Conflicts of Interest Associated With the Use of Predictive Data Analytics by Broker-Dealers and Investment Advisers

Federal RegisterAug 9, 2023

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SECURITIES AND EXCHANGE COMMISSION

17 CFR Parts 240 and 275

[Release Nos. 34-97990; IA-6353; File No. S7-12-23]

RIN 3235-AN00; 3235-AN14

Conflicts of Interest Associated With the Use of Predictive Data Analytics by Broker-Dealers and Investment Advisers

AGENCY:

Securities and Exchange Commission.

ACTION:

Proposed rule.

SUMMARY:

The Securities and Exchange Commission (“Commission” or “SEC”) is proposing new rules (“proposed conflicts rules”) under the Securities Exchange Act of 1934 (“Exchange Act”) and the Investment Advisers Act of 1940 (“Advisers Act”) to eliminate, or neutralize the effect of, certain conflicts of interest associated with broker-dealers' or investment advisers' interactions with investors through these firms' use of technologies that optimize for, predict, guide, forecast, or direct investment-related behaviors or outcomes. The Commission is also proposing amendments to rules under the Exchange Act and Advisers Act that would require firms to make and maintain certain records in accordance with the proposed conflicts rules.

DATES:

Comments should be received on or before October 10, 2023.

ADDRESSES:

Comments may be submitted by any of the following methods:

Electronic Comments

• Use the Commission's internet comment form (

https://www.sec.gov/rules/proposed.shtml

); or

• Send an email to

rule-comments@sec.gov

. Please include File Number S7-12-23 on the subject line.

Paper Comments

• Send paper comments to Vanessa A. Countryman, Secretary, Securities and Exchange Commission, 100 F Street NE, Washington, DC 20549-1090.

All submissions should refer to File Number S7-12-23. This file number should be included on the subject line if email is used. To help the Commission process and review your comments more efficiently, please use only one method of submission. The Commission will post all comments on the Commission's website (https://www.sec.gov/rules/proposed.shtml). Comments are also available for website viewing and printing in the Commission's Public Reference Room, 100 F Street NE, Washington, DC 20549, on official business days between the hours of 10 a.m. and 3 p.m. Operating conditions may limit access to the Commission's Public Reference Room. Do not include personal identifiable information in submissions; you should submit only information that you wish to make available publicly. We may redact in part or withhold entirely from publication submitted material that is obscene or subject to copyright protection.

Studies, memoranda, or other substantive items may be added by the Commission or staff to the comment file during this rulemaking. A notification of the inclusion in the comment file of any such materials will be made available on the Commission's website. To ensure direct electronic receipt of such notifications, sign up through the “Stay Connected” option at www.sec.gov to receive notifications by email.

FOR FURTHER INFORMATION CONTACT:

Blair B. Burnett, Senior Counsel, Investment Company Regulation Office, Michael Schrader, Senior Counsel, Chief Counsel's Office, Sirimal R. Mukerjee, Senior Special Counsel, and Melissa Roverts Harke, Assistant Director, Investment Adviser Regulation Office, Division of Investment Management, at (202) 551-6787 or

IArules@sec.gov

, and Kyra Grundeman and James Wintering, Special Counsels, Anand Das, Senior Special Counsel, Kelly Shoop, Branch Chief, Devin Ryan, Assistant Director, John Fahey, Deputy Chief Counsel, and Emily Westerberg Russell, Chief Counsel, Office of Chief Counsel, Division of Trading and Markets, at (202) 551-5550 or

tradingandmarkets@sec.gov

, Securities and Exchange Commission, 100 F Street NE, Washington, DC 20549-8549.

SUPPLEMENTARY INFORMATION:

The Commission is proposing for public comment: 17 CFR 240.15l-2 under the Exchange Act

(“proposed rule 240.151-2”) and 17 CFR 275.211(h)(2)-4 under the Advisers Act

(“proposed rule 275.211(h)(2)-4” and, together with proposed rule 240.15l-2, “proposed conflicts rules”); and amendments to 17 CFR 240.17a-3 and 17 CFR 240.17a-4 (“rules 17a-3 and 17a-4”) under the Exchange Act and 17 CFR 275.204-2 under the Advisers Act (“rule 204-2” and, together with the proposed amendments to rules 17a-3 and 17a-4, “proposed recordkeeping amendments”).

Unless otherwise noted, when we refer to the Exchange Act, we are referring to 15 U.S.C. 78, and when we refer to rules under the Exchange Act, we are referring to title 17, part 240 of the Code of Federal Regulations [17 CFR 240].

Unless otherwise noted, when we refer to the Advisers Act, we are referring to 15 U.S.C. 80b, and when we refer to rules under the Advisers Act, we are referring to title 17, part 275 of the Code of Federal Regulations [17 CFR 275].

Table of Contents

I. Introduction

A. Overview

B. Background

1. Evolution in the Investment Industry and its Technology Use

2. Current PDA-Like Technology Use and Expected Growth

3. Commission Protection of Investors as Technology Has Evolved

4. Use of Predictive Data Technologies in Investor Interactions

5. Request for Information and Comment

C. Overview of the Proposal

II. Discussion

A. Proposed Conflicts Rules

1. Scope

2. Identification, Determination, and Elimination, or Neutralization of the Effect of, a Conflict of Interest

3. Policies and Procedures Requirement

B. Proposed Recordkeeping Amendments

III. Economic Analysis

A. Introduction

B. Broad Economic Considerations

C. Economic Baseline

1. Affected Parties

2. Technology and Market Practices

3. Regulatory Baseline

D. Benefits and Costs

1. Benefits

2. Costs

E. Effects on Efficiency, Competition, and Capital Formation

1. Efficiency

2. Competition

3. Capital Formation

F. Reasonable Alternatives

1. Expressly Permit, or Require, the Use of Independent Third-Party Analyses

2. Require That Senior Firm Personnel and/or Specific Technology Subject-Matter Experts Participate in the Process of Adopting and Implementing These Policies and Procedures

3. Provide an Exclusion for Technologies That Consider Large Datasets Where Firms Have No Reason To Believe the Dataset Favors the Interests of the Firm From the Identification, Evaluation, and Testing Requirements

4. Apply the Requirements of the Proposed Conflicts Rule and Proposed Recordkeeping Amendments Only to Broker-Dealer Use of Covered Technologies That Have Non-Recommendation Investor Interaction

5. Require That Firms Test Covered Technologies on an Annual Basis, or at a Specific Minimum Frequency

6. Require That Firms Provide a Prescribed and Standardized Disclosure

G. Request for Comment

IV. Paperwork Reduction Act

A. Introduction

B. Proposed Conflicts Rules and Proposed Recordkeeping Amendments

C. Request for Comment

V. Initial Regulatory Flexibility Analysis

A. Reason for and Objectives of the Proposed Action

1. Proposed Rules 151-2 and 211(h)(2)-4

2. Proposed Amendments to Rules 17a-3 and 17a-4 and Rule 204-2

B. Legal Basis

C. Small Entities Subject to the Rules and Rule Amendments

1. Small Advisers Subject to Proposed Rule 211(h)(2)-4 and Proposed Amendments to Recordkeeping Rule

D. Small Broker-Dealers Subject to Proposed Conflicts Rule and Amendments to Recordkeeping Rules

E. Projected Reporting, Recordkeeping, and Other Compliance Requirements

1. Proposed Conflicts Rules

2. Proposed Amendments to Rule 204-2

3. Proposed Amendments to Rules 17a-3 and 17a-4

F. Duplicative, Overlapping, or Conflicting Federal Rules

1. Proposed Rule 211(h)(2)-4 and Proposed Amendments to Rule 204-2

2. Proposed Rule 15l-2 and Proposed Amendments to Rules 17a-3 and 17a-4

G. Significant Alternatives

H. Solicitation of Comments

VI. Consideration of Impact on the Economy

Statutory Authority

Text of Proposed Rules and Form Amendments

I. Introduction

The adoption and use of newer technologies, such as predictive data analytics (“PDA”), by broker-dealers and investment advisers (together, “firms”) have accelerated.

In some instances, firms' use of PDA and similar technologies may be subject to statutory or regulatory investor protections, but in other cases, it may not. Firms' use of PDA-like technologies can bring benefits in market access, efficiency, and returns. To the extent that firms are using PDA-like technologies to optimize for their own interests in a manner (intentionally or unintentionally) that places these interests ahead of investor interests, however, investors can suffer harm. Further, due to the scalability of these technologies and the potential for firms to reach a broad audience at a rapid speed, as discussed below, any resulting conflicts of interest could cause harm to investors in a more pronounced fashion and on a broader scale than previously possible.

See

Deloitte, Artificial intelligence: The next frontier for investment management firms (Feb. 5, 2019),

https://www.deloitte.com/global/en/Industries/financial-services/perspectives/ai-next-frontier-in-investment-management.html

(“AI is providing new opportunities which extend far beyond cost reduction and efficient operations. Many investment management firms have taken note and are actively testing the waters, applying cognitive technologies and AI to various business functions across the industry value chain.”); Blake Schmidt and Amanda Albright,

AI Is Coming for Wealth Management. Here's What That Means, Bloomberg Markets

(Apr. 21, 2023),

https://www.bloomberg.com/news/articles/2023-04-21/vanguard-fidelity-experts-explain-how-ai-is-changing-wealth-management

(discussing experts views on AI impact on the wealth management industry). As discussed more below, in addition to PDA, firms have adopted and used artificial intelligence (“AI”), including machine learning, deep learning, neural networks, natural language processing (“NLP”), or large language models (including generative pre-trained transformers or “GPT”), as well as other technologies that make use of historical or real-time data, lookup tables, or correlation matrices (collectively, “PDA-like technologies”).

See, e.g.,

Q. Zhu and J. Luo,

Generative Pre-Trained Transformer for Design Concept Generation: An Exploration,

Proceedings of the Design Society, Design Vol 2 (May 2022),

https://www.cambridge.org/core/journals/proceedings-of-the-design-society/article/generative-pretrained-transformer-for-design-concept-generation-an-exploration/41894D82DCBC0610B5B6E68967B7047F

(“GPT are language models pre-trained on vast quantities of textual data and can perform a wide range of language-related tasks.”) (citations omitted).

See infra

section I.C.

We believe the current regulatory framework should be updated to help ensure that firms are appropriately addressing conflicts of interests associated with the use of PDA-like technologies. As a result, we are proposing specific protections to complement those already required under existing regulatory frameworks

to better protect investors from harms arising from these conflicts.

See infra

section III.C.3.

A. Overview

Broker-dealers may have a range of conflicts of interest with their retail investors.

Likewise, investment advisers may have conflicts of interest with respect to advisory clients and investors in their pooled investment vehicle clients.

Some of these conflicts of interest are inherent to the relationship between these firms and investors. For example, an investment adviser that is paid a percentage fee based on assets under management has an incentive to encourage a client to move assets into his or her advisory account, which could conflict with investors' interest, for example, to retain assets in a 401(k) plan or other retirement account. Similarly, a broker-dealer that receives transaction-based (

e.g.,

commission) compensation has an incentive to maximize the frequency of transactions, which could increase costs to the investor or expose them to other risks associated with excess trading.

While the proposed conflicts rules do not use or define the term “retail investors,” we use that term in this release to mean “a natural person, or the legal representative of such natural person, who seeks to receive or receives services primarily for personal, family or household purposes,” which is consistent with the definition of “retail investor” in Form CRS and would include both current and prospective retail customers.

See

Form CRS, Sec. 11.E. Separately, we note that, for broker-dealers, the proposed conflicts rule defines “investor” consistent with the definition of “retail investor” in Form CRS.

Proposed rule 275.211(h)(2)-4 would apply to clients and prospective clients of advisers as well as investors and prospective investors in pooled investment vehicles advised by those advisers.

Many broker-dealers and investment advisers also have conflicts of interest associated with other common business practices. For example, some investment product sponsors offer revenue sharing payments, creating an incentive for broker-dealers and investment advisers that accept such payments to favor those investments. Similarly, firms that offer proprietary products have an incentive to favor those products over other non-proprietary alternatives. Dual registrant and affiliated firms that offer both brokerage and advisory accounts have an incentive to steer investors toward the account type that is most profitable for the firm, regardless of whether it is in the best interest of the investor. Unless adequately addressed, these conflicts of interest can cause broker-dealers and investment advisers to place their interests ahead of investors' interests.

Broker-dealers and investment advisers operate within regulatory frameworks that in many cases require them to, as applicable, disclose, mitigate, or eliminate conflicts.

These regulatory frameworks play a fundamental role in protecting retail investors of broker-dealers, clients of investment advisers, and investors in pooled investment vehicle clients of investment advisers (together, “investors”) from the negative effects of firms placing their own interests ahead of investors' interests. As the markets grow and evolve, however, and specifically, as firms adopt and utilize newer technologies to interact with investors, we are evaluating our regulations' effectiveness in protecting investors from the potentially harmful impact of conflicts of interest.

See https://www.sec.gov/rules/final/2019/34-86031.pdf,

Exchange Act Release No. 86031 (June 5, 2019) [84 FR 33318 (July 12, 2019)] (“Reg BI Adopting Release”); Commission Interpretation Regarding Standard of Conduct for Investment Advisers, Advisers Act Release No. 5248 (June 5, 2019) [84 FR 33669 (July 12, 2019)], at section II.C. (“Fiduciary Interpretation”) (describing an adviser's fiduciary duties to its clients). Additionally, rule 206(4)-8 under the Advisers Act prohibits certain statements, omissions, and other acts, practices, or courses of business as fraudulent, deceptive, or manipulative with respect to any investor or prospective investor in a pooled investment vehicle.

Recently, firms' adoption and use of PDA-like technologies

have

accelerated.

While this adoption and use can bring potential benefits for firms and investors (

e.g.,

with respect to efficiency of operations, which can generate cost savings for investors, or enhancing the efficiency of identifying investment opportunities that match an investor's preferences, profile, and risk tolerances), they also raise the potential for conflicts of interest associated with the use of these technologies to cause harm to investors more broadly than before.

Artificial intelligence is generally used to mean the capability of a machine to imitate intelligent human behavior and machine learning is a subfield of artificial intelligence that gives computers the

ability to learn without explicitly being programmed.

See generally

Sara Brown,

Machine Learning, Explained,

MIT Sloan School of Management (Apr. 21, 2021),

https://mitsloan.mit.edu/ideas-made-to-matter/machine-learning-explained.

Predictive data analytics draws inferences from large data sets, relying on hypothesis-free data mining and inductive reasoning to uncover patterns to make predictions about future outcomes, and may use natural language processing, signal processing, topic modeling, pattern recognition, machine learning, deep learning, neural networks, and other advanced statistical methods.

See

Nathan Cortez,

Predictive Analytics Law and Policy: Mapping the Terrain: Challenging Issues in Specific Private Sector Contexts, Substantiating Big Data in Health Care,

14 ISJLP 61, 65 (Fall 2017).

See generally

Financial Industry Regulatory Authority, Inc. (“FINRA”), Artificial Intelligence (AI) in the Securities Industry 5 (June 2020) (“FINRA AI Report”),

https://www.finra.org/sites/default/files/2020-06/ai-report-061020.pdf;

Financial Stability Board, Artificial Intelligence and Machine Learning in Financial Services: Market Developments and Financial Stability Implications (Nov. 1, 2017) (“FSB AI Report”),

https://www.fsb.org/wp-content/uploads/P011117.pdf; see also

Department of the Treasury, et al., Request for Information and Comment on Financial Institutions' Use of Artificial Intelligence, Including Machine Learning (Feb. 2021) [86 FR 16837, 16839-40 (Mar. 31, 2021)] (“Treasury RFI”).

See infra

section I.B.

See, e.g., For AI in Asset Management, Tomorrow is Here,

Markets Media (Mar. 28, 2023),

https://www.marketsmedia.com/for-ai-in-asset-management-tomorrow-is-here/

(citing possible benefits for investment managers in generating alpha, improving efficiency, enhancing product and content distribution, and enhancing risk management and customer experience); Christine Schmid,

AI in Wealth: from Science Fiction to Science Fact,

FinExtra (June 8, 2023),

https://www.finextra.com/blogposting/24323/ai-in-wealth-from-science-fiction-to-science-fact

(citing potential benefits in personalized portfolio creation, enhanced investor engagement, democratized personalized investing, and reduced information overload).

While the presence of conflicts of interest between firms and investors is not new, firms' increasing use of these PDA-like technologies in investor interactions may expose investors to unique risks. This includes the risk of conflicts remaining unidentified and therefore unaddressed or identified and unaddressed. The effects of such unaddressed conflicts may be pernicious, particularly as this technology can rapidly transmit or scale conflicted actions across a firm's investor base.

For example, conflicts of interest can arise from the data the technology uses (including any investor data) and the inferences the technology makes (including in analyzing that data, other data, securities, or other assets). These issues may render a firm's identification of such conflicts for purposes of the firm's compliance with applicable Federal securities laws more challenging without specific efforts both to fully understand the PDA-like technology it is using

and to oversee conflicts that are created by or transmitted through its use of such technology.

See, e.g.,

Sophia Duffy and Steve Parrish, You Say Fiduciary, I Say Binary: A Review and Recommendation of Robo-Advisors and the Fiduciary and Best Interest Standards, 17 Hastings Bus. L.J. 3, at 26 (2021) (stating that the impact of firm conflicts of robo-advisors “are arguably more detrimental than personal conflicts between an advisor and client because the number of clients impacted by the firm conflict is potentially exponentially higher.”) (“Robo-Advisors and the Fiduciary and Best Interest Standards”).

See, e.g., infra

section II.A.2.b and II.A.3 (discussing the testing and policies and procedures requirements, respectively, of the proposed conflicts rules, which if implemented in accordance with the proposal, would necessitate firms' developing an understanding of the PDA-like technologies they use).

See, e.g.,

Sohnke M. Bartram, Jurgen Branke & Mehrshad Motahari,

Artificial Intelligence in Asset Management

(2020) (“AI in Asset Management”) (“Understanding and explaining the inferences made by most AI models is difficult, if not impossible. As the complexity of the task or the algorithm grows, opacity can render human supervision ineffective, thereby becoming an even more significant problem.”).

Moreover, PDA-like technologies may have the capacity to process data, scale outcomes from analysis of data, and evolve at rapid rates.

While valuable in many circumstances, these technologies could rapidly and exponentially scale the transmission of any conflicts of interest associated with such technologies to investors.

For example, a firm may use PDA-like technologies to automatically develop advice and recommendations that are then transmitted to investors through the firm's chatbot, push notifications on its mobile trading application (“app”), and robo-advisory platform. If the advice or recommendation transmitted is tainted by a conflict of interest because the algorithm drifted

to advising or recommending investments more profitable to the firm or because the dataset underlying the algorithm was biased toward investments more profitable to the firm, the transmission of this conflicted advice and recommendations could spread rapidly to many investors.

See, e.g.,

Eray Elicik,

Artificial Intelligence vs. Human Intelligence: Can a game-changing technology play the game?

(Apr. 20, 2022),

https://dataconomy.com/2022/04/is-artificial-intelligence-better-than-human-intelligence/

(“Compared to the human brain, machine learning (ML) can process more data and do so at a faster rate.”); David Nield,

Google Engineers ‘Mutate' AI to Make It Evolve Systems Faster Than We Can Code Them

(Apr. 17, 2020),

https://www.sciencealert.com/coders-mutate-ai-systems-to-make-them-evolve-faster-than-we-can-program-them

(“[R]esearchers have tweaked [a machine learning system] to incorporate concepts of Darwinian evolution and shown it can build AI programs that continue to improve upon themselves faster than they would if humans were doing the coding.”).

See

Robo-Advisors and the Fiduciary and Best Interest Standards,

supra

note 12, at 26.

See also

FINRA AI Report,

supra

note 9 (discussing exploration of the use of AI tools by market participants and noting, among other things, that firms should ensure sound governance and supervision, including effective means of overseeing suitability of recommendations, conflicts of interest, customer risk profiles and portfolio rebalancing) (internal quotations and citation omitted); Y. Minsky, Communications of the ACM, OCaml for the Masses (Sept. 27, 2011),

https://dl.acm.org/doi/pdf/10.1145/2018396.2018413

(explaining that “technology carries risk. There is no faster way for a trading firm to destroy itself than to deploy a piece of trading software that makes a bad decision over and over in a tight loop” and that the author's employer seeks to control these risks by “put[ting] a very strong focus on building software that was easily understood—software that was readable.”).

See infra

note 157 and accompanying text.

Unless adequately addressed, the use of these PDA-like technologies may create or transmit conflicts of interest that place a firm's interests ahead of investors' interests. This may arise not only when a firm is providing investment advice or recommendations, but also in the firm's sales practices and investor interactions more generally, such as design elements, features, or communications that nudge or prompt more immediate and less informed action by the investor.

In light of these developments and risks, and for the reasons we describe further below, we are proposing that a firm's use of certain PDA-like technologies in an investor interaction that places the firm's interests ahead of the investors' interests involves a conflict of interest that must be eliminated or its effects neutralized in accordance with the proposed conflicts rules.

See, e.g.,

CFA Institute,

Ethics and Artificial Intelligence in Investment Management: A Framework for Professionals

(2022) (stating that professionals should ensure they understand the sources of any potential conflicts generated by the use of algorithms and work with developers to ensure that such systems do not inappropriately incorporate fee considerations in the algorithm generating the investment advice).

B. Background

1. Evolution in the Investment Industry and Its Technology Use

Over the last several decades, firms' use of technology to interact with investors and provide products and services has evolved significantly, and with it, the nature and extent of the conflicts of interest this use can create. When Congress first enacted the

Exchange Act and the Advisers Act, firms were increasingly deploying what were then considered advanced technologies, such as punch cards and telex machines. As technology improved, firms began adopting other technologies, such as computers, email, spreadsheets, and the internet. The Commission has previously observed that these and other technologies have helped to promote transparency, liquidity, and efficiency in our capital markets.

If responsibly implemented and overseen by firms, new technologies can aid firms' interactions with investors, and bring greater access and product choice, potentially at a lower cost, without compromising investor protection, capital formation, and fair, orderly, and efficient markets.

See

Interpretation on Use of Electronic Media, Investment Company Act Release No. 24426 (Apr. 28, 2000) [65 FR 25843 (May 4, 2000)], at section I;

see also

Investment Adviser Marketing, Investment Advisers Act No. 5653 (Dec. 22, 2020) [86 FR 13024 (Mar. 5, 2021)], at section I (“Investment Adviser Marketing Release”) (noting that the rules are “designed to accommodate the continual evolution and interplay of technology and advice”).

Where once investors placed trades with their broker in-person, they eventually began to place orders over the phone, and then through a website. Now investors can instantaneously place a trade directly through an app on a smart phone and, instead of a recommendation delivered by a human, they may receive push notifications potentially designed to affect trading behavior. These technological interactions can be designed to respond to human behavior, for example, sending increased notifications for certain investment products depending on where the person scrolling through investment products pauses on her smartphone. As technology continues to evolve, we believe that firms are likely to increase their reliance on behavioral science frameworks in influencing investor behavior.

Investors that previously met in person with their advisers are now able to access computer-generated advice that is delivered rapidly in an app to many investors by, for example, a robo-adviser. Rather than advertising in local newspapers, making cold calls, or relying on referrals, firms are now digitally targeting investors.

See, e.g.,

Robert W. Cook, President and CEO of FINRA,

Statement Before the Financial Services Committee U.S. House of Representatives

(May 6, 2021),

https://www.finra.org/media-center/speeches-testimony/statement-financial-services-committee-us-house-representatives

(addressing the “recent trends of retail trading platforms is the use of ‘game-like' and other features that may encourage investor behaviors” and “the growing prevalence of these features”); Margaret Franklin,

Investment Gamification: Not All Cons, Some Important Pros,

Kiplinger (Feb. 20, 2023),

https://www.kiplinger.com/investing/investment-gamification-pros-and-cons

(discussing the use of behavioral techniques and the rising influence of social media, and stating that the gamification “style of trading, ushered in largely by the next generation of investors, is likely here to stay.”).

See also

James Tierney,

Investment Games,

72 Duke L.J. 353, 355 (Nov. 2022) (describing the growth of retail investing and discussing gamification, including how “mobile app developers have innovated in user-interface design to compete with incumbent brokers [by including features such as] intuitive and appealing design, as well as digital engagement practices that encourage interaction with the app and that shape the information users consider in investing,”); Jill E. Fisch, GameStop and the Reemergence of the Retail Investor, 102 B.U. L. Rev. 1799, 1802 (Oct. 2022) (discussing gamification and the “evidence that retail investment and engagement will both continue and evolve.”); Ernst & Young,

Social investing: behavioral insights for the modern wealth manager

(Apr. 2021),

https://www.ey.com/en_us/wealth-asset-management/social-investing-behavioral-insights-for-the-modern-wealth-manager

(“As firms continue to develop social investing operating models, they can use behavioral science frameworks to better understand how their client segments are influenced by digital design and choice architecture[.]”).

See, e.g.,

Disclosure Innovations in Advertising and Other Communications with the Public, FINRA Regulatory Notice 19-31 (Sept. 19, 2019),

https://www.finra.org/rules-guidance/notices/19-31;

see also

Leslie K. John, Tami Kim, and Kate Barasz,

Ads that Don't Overstep,

Harvard Bus. Rev. (Jan.- Feb. 2018),

https://hbr.org/2018/01/ads-that-dont-overstep.

In recent years, we have observed a rapid expansion in firms' reliance on technology and technology-based products and services.

The use of technology is now central to how firms provide their products and services to investors.

Some firms and investors in financial markets now use new technologies such as AI, machine learning, NLP, and chatbot technologies to make investment decisions and communicate between firms and investors.

In addition, existing technologies for data-analytics and data collection continue to improve and find new applications.

See generally

Marc Andreessen,

Why Software Is Eating the World,

Wall St. J. (Aug. 20, 2011),

http://www.wsj.com/articles/SB10001424053111903480904576512250915629460

(discussing, among other things, the transformation of the financial services industry by software over the last 30 years) (“Why Software is Eating the World”); Robo-Advisors and the Fiduciary and Best Interest Standards,

supra

note 12, at 4 (stating that “[o]ver the past decade, robo-advisors, or automated systems for providing financial advice and services, are becoming more and more popular” and discussing estimated growth); Nicole G. Iannarone,

Fintech's Promises and Perils Computer as Confidant: Digital Investment Advice and the Fiduciary Standard,

93 Chi.-Kent L. Rev. 141, 141 (2018) (“Automated investment advisers permeate the investment industry. Digital investment advisers are the fastest growing segment of financial technology (FinTech) and are disrupting traditional investment advisory delivery models.”) (citations omitted).

See, e.g.,

Investment Adviser Marketing Release,

supra

note 19, at section I (“The concerns that motivated the Commission to adopt the advertising and solicitation rules [in 1961 and 1979, respectively] still exist today, but investment adviser marketing has evolved with advances in technology. In the decades since the adoption of both the advertising and solicitation rules, the use of the internet, mobile applications, and social media has become an integral part of business communications. Consumers today often rely on these forms of communication to obtain information, including reviews and referrals, when considering buying goods and services. Advisers and third parties also rely on these same types of outlets to attract and refer potential customers.”); FINRA Investor Education Foundation,

Investors in the United States: The Changing Landscape

(Dec. 2022)

https://www.finrafoundation.org/sites/finrafoundation/files/NFCS-Investor-Report-Changing-Landscape.pdf

(discussing, among others, website and mobile app use for placing trades and use of social media sites for obtaining investment information).

Michael Kearns & Yuriy Nevmyvaka

Machine Learning for Market Microstructure and High Frequency Trading,

High Frequency Trading—New Realities for Traders, Markets and Regulators (David Easley, Marcos Lopez de Prado & Maureen O'Hara editors, Risk Books, 2013);

see also

Christian Thier & Daniel dos Santos Monteiro,

How Much Artificial Intelligence Do Robo-Advisors Really Use?

(Aug. 31, 2022),

https://ssrn.com/abstract=4218181;

Imani Moise,

Bond Investing Gets the Robo-Adviser Treatment,

The Wall Street Journal (June 7, 2023),

https://www.wsj.com/articles/buying-bonds-is-hard-heres-a-way-to-let-a-robot-do-it-70a4587b.

Natasha Lekh & Petr Pátek,

What's the Future of Web Scraping in 2023?,

APIFY Blog (Jan. 20, 2023),

https://blog.apify.com/future-of-web-scraping-in-2023/;

Jon Martindale,

Best Apps to Use GPT-4, Digitaltrends

(May 4, 2023),

https://www.digitaltrends.com/computing/best-apps-to-use-gpt-4/.

2. Current PDA-Like Technology Use and Expected Growth

Financial market participants currently use AI and machine learning technologies in a variety of ways. For example, algorithmic trading is a widely used application of machine learning in finance, where machine-learning models analyze large datasets and identify patterns and signals to optimize for, predict, guide, forecast, or direct investment-related behaviors or outcomes.

Moreover, the advent and growth of services available on certain digital platforms, such as those offered by online brokerages and robo-advisers, have multiplied the opportunities for retail investors, in particular, to invest and trade in securities, and in small amounts through fractional shares.

This increased accessibility has been one of the key factors associated with the increase of retail investor participation in U.S. securities markets in recent years.

Firms have also expanded their use of technology to include “digital engagement practices” or “DEPs,” such as behavioral prompts, differential marketing, game-like features (commonly referred to as “gamification”), and other design elements or features designed to engage retail investors when using a firm's digital platforms (

e.g.,

website, portal, app)

for services such as trading, robo-advice, and financial education. Our staff has observed that firms use technology to more efficiently develop investment strategies, including by using technology to automate their services, and to analyze the success of specific features and marketing practices at influencing retail investor behavior.

Firms may also seek to lower expenses by replacing customer service personnel with chatbots that can address common customer questions, and outsourcing their back office operations to vendors that rely heavily on technology.

See generally

Alessio Azzutti, Wolf-Goerge Ringe, H. Siegfried Stiehl,

Machine Learning, Market Manipulation, and Collusion on Capital Markets: Why the “Black Box” Matters,

43 U. Pa. J. Int'l L. 1 (2021),

https://scholarship.law.upenn.edu/cgi/viewcontent.cgi?article=2035&context=jil

(“Machine Learning and Market Manipulation”) (discussing current uses of algorithmic trading and exploring the risks to market integrity in connection with the evolving uses of artificial intelligence in algorithmic trading).

See, e.g.,

Nolan Schloneger,

A Case for Regulating Gamified Investing,

56 Ind. L. Rev. 175 (2022) (“Th[e] rise [of investing applications] is largely attributed to zero commission and

fractional-share trading.”); John Csiszar,

How Our Approach to Investing Has Changed Forever,

YAHOO! (Mar. 10, 2021),

https://www.yahoo.com/now/approach-investing-changed-forever-190007929.html

(“Fractional share trading is just in its infancy but appears well on its way to changing how consumers approach investing. With fractional share trading, you can invest any dollar amount into stock, even if you don't have enough to buy a single share . . . . Fractional share investing allows nearly anyone to get involved in the stock market without needing $100,000 or more to buy a properly diversified portfolio of individual stock names.”).

See also

Staff Report on Equity and Options Market Structure Conditions in Early 2021 (Oct. 14, 2021),

https://www.sec.gov/files/staff-report-equity-options-market-struction-conditions-early-2021.pdf

(“Some brokers have sought to attract new customers by offering the ability to purchase fractional shares. Fractional shares give investors the ability to purchase less than 1 share of a stock.”). Any staff statements represent the views of the staff. They are not a rule, regulation, or statement of the Commission. Furthermore, the Commission has neither approved nor disapproved their content. These staff statements, like all staff statements, have no legal force or effect: they do not alter or amend applicable law; and they create no new or additional obligations for any person.

See, e.g.,

Maggie Fitzgerald,

Retail Investors Continue to Jump Into the Stock Market After GameStop Mania,

CNBC (Mar. 10, 2021),

https://www.cnbc.com/2021/03/10/retail-investor-ranks-in-the-stock-market-continue-to-surge.html

(providing year-over-year app download statistics for Robinhood, Webull, Sofi, Coinbase, TD Ameritrade, Charles Schwab, E-Trade, and Fidelity from 2018-2020, and monthly figures for January and February of 2021); John Gittelsohn,

Schwab Boosts New Trading Accounts 31% After Fees Go to Zero,

Bloomberg (Nov. 14, 2019),

https://www.bloomberg.com/news/articles/2019-11-14/schwab-boosts-brokerage-accounts-by-31-after-fees-cut-to-zero

(noting that Charles Schwab opened 142,000 new trading accounts in October, a 31% jump over September's pace).

Examples of DEPs include the following: social networking tools; games, streaks and other contests with prizes; points, badges, and leaderboards; notifications; celebrations for trading; visual cues; ideas presented at order placement and other curated lists or features; subscriptions and membership tiers; and chatbots.

See, e.g.,

SEC Investor Bulletin: Robo-Advisers (Feb. 23, 2017),

https://www.sec.gov/oiea/investor-alerts-bulletins/ib_robo-advisers

(discussing automated digital investment advisory programs);

see also

FINRA AI Report,

supra

note 9 (discussing three areas where broker-dealers are evaluating or using AI in the securities industry: communications with customers, investment processes, and operational functions).

See, e.g., SS&C Gets Automation Rolling with 180 `Digital Workers',

Ignites (Feb. 9, 2023),

https://www.ignites.com/c/3928224/508304?referrer_module=searchSubFromIG&highlight=SS&C.

The rate at which PDA-like technologies continues to evolve is increasing

and firms are exploring and deploying AI-based applications across different functions of their organizations, including customer facing, investment, and operational activities.

These PDA-like technologies are complex and may include several categories of machine learning

algorithms, such as deep learning,

supervised learning,

unsupervised learning,

and reinforcement learning

processes.

In the past few years, these PDA-like technologies have made increasing use of natural language processing and natural language generation.

For example, AI has revolutionized chatbots by enabling them to understand and respond to natural language more accurately and learn and improve responses over time, leading to more personalized interactions with users. Recently, a new wave of online chatbots has rapidly moved machines using AI into new territory.

Some of these chatbots have passed what is known as the “Turing test” and have become virtually indistinguishable from humans in particular situations.

AI use is increasing year over year and in an array of applications.

For instance, some robo-advisers use chatbots and NLP technology for their online platforms to provide investment advice and manage investment portfolios.

These platforms may use a combination of AI, machine learning, NLP, and chatbot technologies to provide personalized investment recommendations to customers based on customer risk tolerance and investment goals.

See, e.g.,

Robin Feldman and Kara Stein,

AI Governance in the Financial Industry,

27 Stan. J.L. Bus. & Fin. 94, 122 (2022) (describing AI as “a technology that is rapidly evolving and capable of learning.”).

See, e.g.,

Merav Ozair,

FinanceGPT: The Next Generation of AI-Powered Robo Advisors and Chatbots

(June 27, 2023),

https://www.nasdaq.com/articles/financegpt-the-next-generation-of-ai-powered-robo-advisors-and-chatbots

(describing current uses and development) (“FinanceGPT”).

FINRA described “Machine Learning (ML)” as “a field of computer science that uses algorithms to process large amounts of data and learn from it. Unlike traditional rules-based programming, [machine learning] models learn from input data to make predictions or identify meaningful patterns without being explicitly programmed to do so. There are different types of [machine-learning] models, depending on their intended function and structure[.]”

See

FINRA AI Report,

supra

note 9.

FINRA described a “deep learning model” as a model “built on an artificial neural network, in which algorithms process large amounts of unlabeled or unstructured data through multiple layers of learning in a manner inspired by how neural networks function in the brain. These models are typically used when the underlying data is significantly large in volume, obtained from disparate sources, and may have different formats (

e.g.,

text, voice, and video).”

See id.

FINRA described a “supervised machine learning” as a model that “is trained with labeled input data that correlates to a specified output. . . . The model is continuously refined to provide more accurate output as additional training data becomes available. After the model has learned from the patterns in the training data, it can then analyze additional data to produce the desired output . . . .”

See id.

As described by FINRA, in unsupervised machine learning, “the input data is not labeled nor is the output specified. Instead, the models are fed large amounts of raw data and the algorithms are designed to identify any underlying meaningful patterns. The algorithms may cluster similar data but do so without any preconceived notion of the output . . . .”

See id.

As described by FINRA, in reinforcement learning, “the model learns dynamically to achieve the desired output through trial and error. If the model algorithm performs correctly and achieves the intended output, it is rewarded. Conversely, if it does not produce the desired output, it is penalized. Accordingly, the model learns over time to perform in a way that maximizes the net reward . . . .”

See id.

See also

FSB AI Report,

supra

note 9; Treasury RFI,

supra

note 9.

See, e.g.,

FINRA AI Report,

supra

note 9.

See

Cade Metz,

How Smart Are the Robots Getting?,

The New York Times (Jan. 20, 2023, updated Jan. 25, 2023).

Id.

The Turing test is a subjective test determined by whether the person interacting with a machine believes that they are interacting with another person.

See id.

Embracing the Rapid Pace of AI,

MIT Technology Review Insights (May 19, 2021),

https://www.technologyreview.com/2021/05/19/1025016/embracing-the-rapid-pace-of-ai/.

See, e.g.,

FinanceGPT,

supra

note 33 (describing current uses and development).

As a result of a growing desire to perform functions remotely and through automated means, the COVID-19 pandemic accelerated the adoption of certain PDA-like technologies.

Many

expect this momentum to continue, with AI becoming a mainstream technology across many industries, including the financial sector.

Organizations, including firms in the securities industry,

are using AI in a multitude of ways, including responding to customer inquiries, automating back-office processes, quality control,

risk management, client identification and monitoring, selection of trading algorithms, and portfolio management.

Others are actively developing investment advisory services based on PDA-like technologies.

Further, recent advancements in data collection techniques have significantly enhanced the scale and scope of data analytics, and its potential applications. Due to increases in processing power and data storage capacity, a vast amount of data is now available for high-speed analysis using these technologies.

Furthermore, the range of data types has also expanded, with consumer shopping histories, media preferences, and online behavior now among the many types of data that data analytics can use to synthesize information, forecast financial outcomes, and predict investor and customer behavior.

Consequently, these technologies can be applied in novel and powerful ways which may be subtle, such as using the layout of an app and choice of data presentation and formatting to influence trading decisions.

Some trading apps use PDA and AI/machine learning along with detailed user data to increase user engagement and trading activity.

See, e.g.,

Joe McKendrick,

AI Adoption Skyrocketed Over the Last 18 Months,

Harvard Bus. Rev. (Sept. 27, 2021),

https://hbr.org/2021/09/ai-adoption-skyrocketed-over-the-last-18-months

(“The [COVID-19] crisis accelerated the adoption of analytics and AI, and this momentum will continue into the 2020s, surveys show. Fifty-two percent of companies accelerated their AI adoption plans because of the Covid crisis, a study by PwC finds. Just about all, 86%, say that AI is becoming a `mainstream technology' at their company in 2021. Harris Poll, working with Appen, found that 55% of companies reported they accelerated their AI strategy in 2020 due to Covid, and 67% expect to further accelerate their AI strategy in 2021.”);

KPMG,

Thriving in an AI World: Unlocking the Value of AI Across Seven Key Industries

(May 2021), at 5,

https://advisory.kpmg.us/articles/2021/thriving-in-an-ai-world.html

(“Thriving in an AI World”); Blake Schmidt and Amanda Albright,

AI Is Coming for Wealth Management. Here's What That Means, Bloomberg Markets

(Apr. 21, 2023),

https://www.bloomberg.com/news/articles/2023-04-21/vanguard-fidelity-experts-explain-how-ai-is-changing-wealth-management

(discussing experts views on AI impact on the wealth management industry).

Id.

See

IOSCO,

The use of artificial intelligence and machine learning by market intermediaries and asset managers

(Sept. 2021), at 1 (“IOSCO AI/ML Report”),

iosco.org/library/pubdocs/pdf/IOSCOPD684.pdf

(“Artificial Intelligence (AI) and Machine Learning (ML) are increasingly used in financial services, due to a combination of increased data availability and computing power. The use of AI and ML by market intermediaries and asset managers may be altering firms' business models.”).

See

Thriving in an AI World,

supra

note 45;

see also

FINRA AI Report,

supra

note 9, at 5-10 (noting the use of AI in the securities industry for communications with customers, investment processes, and operational functions); FINRA,

Deep Learning: The Future of the Market Manipulation Surveillance Program

https://www.finra.org/media-center/finra-unscripted/deep-learning-market-surveillance

(“FINRA's Market Regulation and Technology teams recently wrapped up an extensive project to migrate the majority of FINRA's market manipulation surveillance program to using deep learning in what is perhaps the largest application of artificial intelligence in the RegTech space to date.”); Machine Learning and Market Manipulation,

supra

note 26; IOSCO AI/ML Report,

id.

IOSCO AI/ML Report,

supra

note 47.

See, e.g.,

Hugh Son,

JPMorgan is developing a ChatGPT-like A.I. service that gives investment advice, CNBC

(May 25, 2023),

https://www.cnbc.com/2023/05/25/jpmorgan-develops-ai-investment-advisor.html

(discussing a trademark application filed by JPMorgan for a product called IndexGPT that will utilize “cloud computing software using artificial intelligence” for “analyzing and selecting securities tailored to customer needs[.]”).

See, e.g.,

Dimitris Andriosopoulos et al.,

Computational Approaches and Data Analytics in Financial Services: A Literature Review,

70 J. Operational Rsch. Soc. 1581 (2019),

https://doi.org/10.1080/01605682.2019.1595193;

James Lawler & Anthony Joseph,

Big Data Analytics Methodology in the Financial Industry,

15 Info. Sys. Ed. J. 38 (July 2017),

https://isedj.org/2017-15/n4/ISEDJv15n4p38.html.

Daniel Broby,

The Use of Predictive Analytics in Finance,

8 J. Fin & Data Sci. 145 (Nov. 2022),

https://doi.org/10.1016/j.jfds.2022.05.003;

OECD,

Artificial Intelligence, Machine Learning and Big Data in Finance: Opportunities, Challenges, and Implications for Policy Makers

(2021),

https://www.oecd.org/finance/financial-markets/Artificial-intelligence-machine-learning-big-data-in-finance.pdf.

See, e.g.,

Sayan Chaudhury and Chinmay Kulkarni,

Design Patterns of Investing Apps and Their Effects on Investing Behaviors

(2021) (“Chaudhury & Kulkarni”),

dl.acm.org/doi/fullHtml/10.1145/3461778.3462008

(“investing apps can be considered as technical and social choice architectures that influence investing behavior”).

See, e.g.,

Alex McFarland,

10 “Best” AI Stock Trading Bots,

Unite.AI (June 4, 2023),

https://www.unite.ai/stock-trading-bots/.

Any risks of conflicts of interest associated with AI use will expand as firms' use of AI grows. These risks will have broad consequences if AI makes decisions that favor the firms' interests and then rapidly deploys that information to investors, potentially on a large scale.

Firms' nascent use of AI may already be exposing investors to these types of risks as well as others.

We are concerned that firms will intentionally or unintentionally take their own interest into account in the data or software underlying the applicable AI, as well as the applicable PDA-like technologies, resulting in investor harm. Among other things, a firm may use these technologies to optimize for the firm's revenue or to generate behavioral prompts or social engineering to change investor behavior in a manner that benefits the firm but is to the detriment of the investor.

See, e.g.,

Robo-Advisors and the Fiduciary and Best Interest Standards,

supra

note 12 (stating that the impact of firm conflicts of robo-advisors “are arguably more detrimental than personal conflicts between an advisor and client because the number of clients impacted by the firm conflict is potentially exponentially higher.”).

See also

AI in Asset Management,

supra

note 14 (“AI can make wrong decisions based on incorrect inferences that have captured spurious or irrelevant patterns in the data. For example, ANNs [artificial neural networks] that are trained to pick stocks with high expected returns might select illiquid, distressed stocks.”); FINRA AI Report,

supra

note 9, at 11-19 (noting that the use of AI “raises several concerns that may be wide-ranging across various industries as well as some specific to the securities industry. Over the past few years, there have been numerous incidents reported about AI applications that may have been fraudulent, nefarious, discriminatory, or unfair, highlighting the issue of ethics in AI applications.”); FINRA AI Report,

supra

note 9, at 13 (“Depending on the use case, data scarcity may limit the model's analysis and outcomes, and could produce results that may be narrow and irrelevant. On the other hand, incorporating data from many different sources may introduce newer risks if the data is not tested and validated, particularly if new data points fall outside of the dataset used to train the model.”).

See, e.g.,

FINRA AI Report,

supra

note 9, at 5 (“The use of AI-based applications is proliferating in the securities industry[.]”); Sophia Duffy and Steve Parrish,

You Say Fiduciary, I Say Binary: A Review and Recommendation of Robo-Advisors and the Fiduciary and Best Interest Standards,

17 Hastings Bus. L.J. 3, at 26 (2021) (“robo-advisors can be, and often are, intentionally programmed to favor the institution by making recommendations that favor the institution's products, rebalance client portfolios in ways which will allow the institution to earn more fees, and otherwise make recommendations that benefit the firm”).

3. Commission Protection of Investors as Technology Has Evolved

As noted above, firms' use of technology and subsequent adaptation incorporating emerging technologies are not new.

At the same time, the Commission has addressed firms' relationships with investors in a variety of ways to ensure investor protection as use of technology in those relationships has evolved over time.

The proposal, thus, is consistent with the Commission's practice of evolving our regulation in light of market and technological developments.

See supra

section I.B.2.

See infra

note 114.

Broker-dealers and investment advisers are currently subject to extensive obligations under Federal securities laws and regulations, and, in the case of broker-dealers, rules of self-regulatory organizations,

that are

designed to promote conduct that, among other things, protects investors, including protecting investors from conflicts of interest.

To the extent PDA-like technologies are used in investor interactions that are subject to existing obligations, those obligations apply. These obligations include, but are not limited to, obligations related to investment advice and recommendations;

general and specific requirements aimed at addressing certain conflicts of interest, including requirements to eliminate, mitigate, or disclose certain conflicts of interest; disclosure of firms' services, fees, and costs; disclosure of certain business practices, advertising, communications with the public (including the use of “investment analysis tools”); supervision; and obligations related to policies and procedures.

In addition to these obligations, Federal securities laws and regulations broadly prohibit fraud by broker-dealers and investment advisers as well as fraud by any person in the offer, purchase, or sale of securities, or in connection with the purchase or sale of securities.

Any person operating as a “broker” or “dealer” in the U.S. securities markets must register with the Commission, absent an exception or exemption.

See

Exchange Act section 15(a), 15 U.S.C. 78

(a);

see also

Exchange Act sections 3(a)(4) and 3(a)(5), 15 U.S.C. 78c(a)(4) and 78c(a)(5) (definitions of “broker” and “dealer,” respectively). Generally, all registered broker-dealers that deal with the public must become members of FINRA, a registered national securities association, unless the broker or dealer effects transactions in securities solely on an exchange of which it is a member.

See

Exchange Act section 15(b)(8), 15 U.S.C. 78o(b)(8);

see also

17 CFR 240.15b9-1 (providing an exemption from Section 15(b)(8)). FINRA is the sole national securities association registered with the SEC under Section 15A of the Exchange Act. Because this release is focused on broker-dealers that deal with

the public and are FINRA member firms (unless an exception applies), we refer to FINRA rules as broadly applying to “broker-dealers,” rather than to “FINRA member firms.”

See infra

section III.C.3; Fiduciary Interpretation,

supra

note 8, at section II.C. (“The duty of loyalty requires that an adviser not subordinate its clients' interests to its own.”);

see also

Reg BI Adopting Release,

supra

note 8, at section II.A.1. (The “without placing the financial or other interest . . . ahead of the interest of the retail customer” phrasing recognizes that while a broker-dealer will inevitably have some financial interest in a recommendation—the nature and magnitude of which will vary—the broker-dealer's interests cannot be placed ahead of the retail customer's interest”). Additionally, broker-dealers often provide a range of services that do not involve a recommendation to a retail customer—which is required in order for Reg BI to apply—and those services are subject to general and specific requirements to address associated conflicts of interest under the Exchange Act, Securities Act of 1933, and relevant self-regulatory organization (“SRO”) rules as applicable.

See also

FINRA Report on Conflicts of Interest (Oct. 2013), at Appendix I (Conflicts Regulation in the United States and Selected International Jurisdictions) (“FINRA Conflict Report”),

https://www.finra.org/sites/default/files/Industry/p359971.pdf

(describing broad obligations under SEC and FINRA rules as well as specific conflicts-related disclosure requirements under FINRA rules).

See, e.g.,

17 CFR 240.15l-1(a)(1) (“Exchange Act rule 15l-1(a)(1)”) (requiring broker-dealers and their associated persons to act in the best interest of retail customers when making recommendations, without placing the financial or other interest of the broker-dealer or its associated person ahead of the interest of the retail customer).

Compliance with the proposed conflicts rules would not alter a broker-dealer's or investment adviser's existing obligations under the Federal securities laws. The proposed conflicts rules would apply in addition to any other obligations under the Exchange Act and Advisers Act, along with any rules the Commission may adopt thereunder, and any other applicable provisions of the Federal securities laws and related rules and regulations.

The Commission has long acted to protect investors against the harm that can come when a firm acts on its conflicts of interest.

For example, the Commission has brought enforcement actions regarding an investment adviser's fiduciary duty to its clients with respect to conflicts of interest.

Similarly, the Commission has reinforced fraud protection for investors in pooled investment vehicles against conflicts of interest through rule 206(4)-8.

The Commission regulates investment adviser advertising and marketing practices to protect against, among others, adviser conflicts of interest that may taint such marketing, including through recent amendments adapting those protections in light of the evolution of practices and technologies.

See infra

section III.C.

See, e.g.,

SEC Press Release, SEC Share Class Initiative Returning More Than $125 Million to Investors: Reflecting SEC's Commitment to Retail Investors, 79 Investment Advisers Who Self-Reported Advisers Act Violations Agree to Compensate Investors Promptly, Ensure Adequate Fee Disclosures (Mar. 11, 2019),

https://www.sec.gov/news/press-release/2019-28

(describing settled orders against 79 investment advisers finding that the settling investment advisers placed their clients in mutual fund share classes that charged 12b-1 fees when lower-cost share classes of the same fund were available to their clients without adequately disclosing that the higher cost share class would be selected; according to the SEC's orders, the 12b-1 fees were routinely paid to the investment advisers in their capacity as brokers, to their broker-dealer affiliates, or to their personnel who were also registered representatives, creating a conflict of interest with their clients, as the investment advisers stood to benefit from the clients' paying higher fees);

SEC

Sergei Polevikov, et al.,

Litigation Release No. 25475 (Aug. 17, 2022) (settled order) (final judgment against employee working as a quantitative analyst at two asset management firms “for perpetrating a front-running scheme that generated profits of approximately $8.5 million”); SEC Brings Settled Actions Charging Cherry-Picking and Compliance Failures, Adm. Proc. File No. 3-20955 (Aug 10, 2022) (settled order) (alleged multi-year cherry-picking scheme of former investment adviser representative of registered investment adviser preferentially allocating profitable trades or failing to allocate unprofitable trades to a adviser's personal accounts at the expense of the advisers client accounts).

17 CFR 275.206(4)-8;

see, e.g.,

In re. Virtua Capital Management, LLC, et al., Advisers Act Release No. 6033 (May 23, 2022) (allegedly failing to disclose conflicts of interest and associated fees, and breaching fiduciary duty to multiple private investment funds) (settled order).

See

Investment Adviser Marketing Release,

supra

Likewise, broker-dealers have long been subject to Commission and SRO regulations and rules that govern their business conduct, including general and specific obligations to address conflicts of interest.

For example, under existing antifraud provisions of the Exchange Act, a broker-dealer has a duty to disclose material adverse information to its customers.

Indeed, the Commission has enforced a broker-dealer's duty to disclose material conflicts of interest under the antifraud provisions.

Broker-dealers are subject to specific FINRA rules aimed at addressing certain conflicts of interest.

Moreover, in 2019 the Commission adopted Regulation Best Interest (“Reg BI”), which was designed to enhance the quality of broker-dealer recommendations to retail customers and reduce the potential harm to retail customers that may be caused by conflicts of interest,

by requiring broker-dealers that make recommendations to retail customers to, among other things, establish, maintain, and enforce policies and procedures reasonably designed to identify and

disclose, mitigate, or eliminate, conflicts associated with a recommendation, including conflicts of interest that may result through the use of PDA-like technology to make recommendations (Reg BI's “Conflict of Interest Obligation”).

See infra

section III.C.3

A broker-dealer may be liable if it does not disclose “material adverse facts of which it is aware.”

See, e.g., Chasins

Smith, Barney & Co.,

438 F.2d 1167, 1172 (2nd Cir. 1970);

SEC

Hasho,

784 F. Supp. 1059, 1110 (S.D.N.Y. 1992); In the Matter of RichMark Capital Corp., Exchange Act Release No. 48758 (Nov. 7, 2003) (Commission Opinion) (“When a securities dealer recommends stock to a customer, it is not only obligated to avoid affirmative misstatements, but also must disclose material adverse facts of which it is aware. That includes disclosure of `adverse interests' such as `economic self-interest' that could have influenced its recommendation.”) (citations omitted).

See, e.g.,

In re. Edward D. Jones & Co, Securities Act Release No. 8520 (Dec. 22, 2004) (settled order) (broker-dealer violated antifraud provisions of Securities Act and Exchange Act by failing to disclose conflicts of interest arising from receipt of revenue sharing, directed brokerage payments and other payments from “preferred” families that were exclusively promoted by broker-dealer); In re. Morgan Stanley DW Inc., Securities Act Release No. 8339 (Nov. 17, 2003) (settled order) (broker-dealer violated antifraud provisions of Securities Act by failing to disclose special promotion of funds from families that paid revenue sharing and portfolio brokerage).

FINRA rules establish restrictions on the use of non-cash compensation in connection with the sale and distribution of mutual funds, variable annuities, direct participation program securities, public offerings of debt and equity securities, investment company securities, real estate investment trust programs, and the use of non-cash compensation to influence or reward employees of others.

See

FINRA Rules 2310, 2320, 2331, 2341, 5110, and 3220. These rules generally limit the manner in which members can pay or accept non-cash compensation and detail the types of non-cash compensation that are permissible.

See

Reg BI Adopting Release

supra

note 8, at text accompanying n.21.

17 CFR 240.15l-1(a)(2)(iii) (“Exchange Act rule 15l-1(a)(2)(iii)”).

The Commission has and will continue to bring enforcement actions for violations of the Federal securities laws that entail the use of PDA-like technologies. However, the rapid acceleration of PDA-like technologies and their adoption in the investment industry,

the additional challenges associated with identifying and addressing conflicts of interest resulting from the use of these new technologies, and the concerns relating to scalability, discussed above, reinforce the importance of ensuring our regulatory regime specifically addresses these issues. In particular, disclosure may be ineffective in light of, as discussed above, the rate of investor interactions, the size of the datasets, the complexity of the algorithms on which the PDA-like technology is based, and the ability of the technology to learn investor preferences or behavior, which could entail providing disclosure that is lengthy, highly technical, and variable, which could cause investors difficulty in understanding the disclosure.

See, e.g.,

Amy Caiazza, Rob Rosenblum, and Danielle Sartain,

Investment Advisers' Fiduciary Duties: The Use of Artificial Intelligence,

Harvard Law School Forum on Corporate Governance (June 11, 2020),

https://corpgov.law.harvard.edu/2020/06/11/investment-advisers-fiduciary-duties-the-use-of-artificial-intelligence/

(“Artificial intelligence (AI) is an increasingly important technology within the investment management industry.”); FINRA AI Report,

supra

note 9, at 5 (“The use of AI-based applications is proliferating in the securities industry and transforming various functions within broker-dealers.”).

In light of these concerns, and the harm to investors that can result when firms act on conflicts of interest, we are proposing rules to address conflicts of interest associated with a firm's use of PDA-like technologies when interacting with investors that are contrary to the public interest and the protection of investors. In particular, the recent and rapid expansion of PDA-like technologies in the context of investment-related activities, without specific oversight obligations tailored to the specific risks involved in their use, can lead to outcomes that financially benefit firms at the expense of investors. Such a harm to investors might include the use of PDA-like technologies that prompt investors to enroll in products or services that financially benefit the firm but may not be consistent with their investment goals or risk tolerance, encourage investors to enter into more frequent trades or employ riskier trading strategies (

e.g.,

margin trading) that will increase the firm's profit at the investors' expense, or inappropriately steer investors toward complex and risky securities products inconsistent with investors' investment objectives or risk profiles that result in harm to investors but that financially benefit the firm. Due to the inherent complexity and opacity of these technologies as well as their potential for scaling, we are proposing that such conflicts of interest should be eliminated or their effects should be neutralized, rather than handled by other methods of addressing the conflicts, such as through disclosure and consent. Moreover, many of these technologies provide means—for example, A/B testing

—to empirically assess the conflicts' impact and thus to neutralize the effect of a conflict on investors. Further, reliance on scalable, complex, and opaque PDA-like technologies can result in operational challenges or shortcomings. For example, failure to identify and address conflicts that may be present in the PDA-like technology used to steer investors toward a product or service could result in a firm's failure to identify the risks to investors of certain investing behaviors that place the firm's interest ahead of investors' interest as well as inadequate compliance policies and procedures that would assist the firm in curbing these practices. As a consequence, this could result in the failure to take sufficient steps to address the potentially harmful effect of those conflicts.

For these additional reasons, we are proposing that such conflicts of interest be eliminated or their effects be neutralized, rather than handled by other methods of addressing the conflicts, such as through disclosure and consent.

A/B testing refers to running a learning model on two different datasets with a single change between the two, which can help identify causal relationships and, through understanding how changes affect outcomes, gain a better understanding of the functionality of a model.

See

Seldon, A/B Testing for Machine Learning (July 7, 2021) (“Seldon”),

https://www.seldon.io/a-b-testing-for-machine-learning.

See, e.g.,

William Shaw and Aisha S. Gani,

Wall Street Banks Seizing AI to Rewire the World of Finance,

Financial Review (June 1, 2023) (in discussing fiduciary duty obligation when using AI in finance quoting a law firm partner as saying: “How do you demonstrate to investors and regulators that you've done your duty when you've used an output without really knowing what the inputs are?”).

4. Use of Predictive Data Technologies in Investor Interactions

Firms may use PDA-like technologies to transform user interfaces and the interactions that investors have on digital platforms.

For example, firms may collect data from a variety of internal sources (

e.g.,

trading desks, customer account histories, and communications) and external sources (

e.g.,

public filings, social media platforms, and satellite images) in both structured and unstructured formats,

enabling them to develop an understanding of investor preferences and adapt the interface and related prompts to appeal to those preferences. Firms may use these tools to increase the quantity of information used to support investment ideas,

leverage investor data to send targeted questionnaires to investors regarding evolving investment goals, identify which investors might be open to a new investment product, or identify which investors are most likely to stop using a firm's services.

We are concerned, however, that a firm's use of PDA-like technologies when engaging or communicating with—including by providing information to, providing recommendations or advice to, or soliciting—a prospective or current investor could take into consideration the firm's interest in a manner that places its interests ahead of investors' interests and thus harm investors.

For example, some members of the public have expressed concern that firms' use of these PDA-like technologies encourages practices that are profitable for the firm but may increase investors' costs, undermine investors' performance, or expose investors to

unnecessary risks based on their individual investment profile, such as: (i) excessive trading,

(ii) using trading strategies that carry additional risk (

e.g.,

options trading and trading on margin), and (iii) trading in complex securities products that are more remunerative to the firm but pose undue risk to the investor.

See, e.g.,

FSB AI Report,

supra

note 9, at 14-15 (chatbots are being introduced by a range of financial services firms, often in mobile apps or social media, and chatbots are “increasingly moving toward giving advice and prompting customers to act”).

See

FINRA AI Report,

supra

note 9, at 4.

See

Deloitte,

Artificial intelligence: The next frontier for investment management firms

(Feb. 5, 2019),

https://www.deloitte.com/global/en/Industries/financial-services/perspectives/ai-next-frontier-in-investment-management.html.

See

Ryan W. Neal,

Three Firms Where Artificial Intelligence is Helping with Financial Planning

(Jan. 17, 2020),

https://www.investmentnews.com/artificial-intelligence-advisers-176541

(describing current uses of AI and their potential application to broker-dealers and investment advisers).

While the proposed rules apply more broadly to the use of covered technology in investor interactions, as discussed below, firms using covered technology to provide advice or make recommendations are subject to standards of conduct, among other regulatory obligations, that already apply to such advice or recommendations.

See infra

section III.C.3. The proposed conflicts rules would apply in addition to these standards of conduct and other regulatory obligations.

See, e.g.,

Comment Letter from Pace Investor Rights Clinic (Oct. 1, 2021) (“Pace University Letter”) (“DEPs can lead investors to trade more frequently and more often than is in their best interest. For example, the push notification feature provides investors with live price updates. This intentionally prompts investors to check their portfolios after receiving the notification, which can lead them to make additional trades or spend more time on the platform than they would have otherwise. Traditionally, the goal of investing for most retail investors is to save for the long term. Frequently checking their portfolio may cause investors to make decisions not in line with the goal of long-term saving and generational wealth building.”).

See also

National Institute of Science and Technology Special Publication 1270,

Towards a Standard for Identifying and Managing Bias in Artificial Intelligence

(Mar. 2022), at section 3.1 (describing dataset challenges resulting in AI bias, discrimination, and systematic gaps in performance); Thor Olavsrud,

7 famous analytics and AI disasters

(Apr. 15, 2022),

https://www.cio.com/article/190888/5-famous-analytics-and-ai-disasters.html.

While the risk of poor data quality or skewed data is not unique to AI, the ability of PDA-like technologies used in investor interactions to process data more quickly than humans, and the potential for technology to disseminate the resulting communications to a mass market, can quickly magnify conflicts of interest and any resulting negative effects on investors. Moreover, erroneous data considered by a firm's algorithm could have the effect of optimizing for the firm's interest over investors' interest by, for example, relying on outdated, previously higher cost information of investment options sponsored by other firms but relying on updated, lower cost information of identical investment options sponsored by the firm. This could result in a recommendation, advice, or other investor interaction that favors the firm's sponsored products and creates a conflict, regardless of whether the firm intentionally developed the algorithm to optimize for its interest.

Poor data quality or skewed data could not only limit the learning capability of an AI or machine learning system but could also potentially negatively impact how it makes inferences and decisions in the future,

giving rise to erroneous or poor predictions, resulting in a failure to achieve the system's intended objectives,

and benefiting the firm over investors (whether intentionally or unintentionally).

In this example, it is also possible that erroneous data could result in the reverse effect, generating a recommendation in favor of a non-sponsored product when the firm's sponsored product may be more cost-effective. This would not result in a conflict under the proposed rules but would nonetheless be subject to firms' obligations under their respective regulatory regimes, including the applicable standard of conduct.

See

Artificial Intelligence/Machine Learning Risk & Security Working Group (AIRS),

Artificial Intelligence Risk & Governance,

at 2.1.1 (accessed Apr. 18, 2023) (“AIRS White Paper”),

https://aiab.wharton.upenn.edu/research/artificial-intelligence-risk-governance/.

Id.

We have observed instances where conflicts of interest associated with a firm's use of PDA-like technologies have resulted in harm to investors. A recent enforcement action involved allegations that an adviser marketed that its “no fee” robo-adviser portfolios were determined through a “disciplined portfolio construction methodology” when they allegedly were pre-set to hold a certain percent of assets in cash because the adviser's affiliate was guaranteed a certain amount of revenue at these levels. The adviser allegedly did not disclose its conflict of interest in setting the cash allocations; that this conflict resulted in higher cash allocations, which could negatively impact performance in a rising market; and that the cash allocations were higher than other services because clients did not pay a fee.

While the focus of that action was on the alleged disclosure failure, it also highlights the potential for PDA-like technologies to be used in ways that advance a firm's interests at the expense of its investors' interests. The proposed conflicts rules would require a firm to analyze its investor interactions that use PDA-like technology for the types of conflicts of interest that were at issue in that action in order to determine whether the investor interaction places the firm's interests ahead of its investors' interests and, if so, eliminate, or neutralize the effect of, the conflicts of interest on investors. In addition, the Commission's 2021 Request for Information and Comments on Broker-Dealer and

Investment Adviser Digital Engagement Practices, Related Tools and Methods, and Regulatory Considerations and Potential Approaches (“Request”)

solicited comments related to conflicts of interest, among other areas.

In response, the Commission received comments reflecting perceived conflicts of interest related to the use of online investing and trading applications, which some commenters indicated undermine their faith in the fairness of the markets.

In re. Charles Schwab & Co., Inc., et al., Exchange Act Release No. 95087 (June 13, 2022) (settled order).

See

Request for Information and Comments on Broker-Dealer and Investment Adviser Digital Engagement Practices, Related Tools and Methods, and Regulatory Considerations and Potential Approaches, Exchange Act Release No. 92766 (Aug. 27, 2021) [86 FR 49067 (Sept. 1, 2021)].

See id.,

questions 1.26, 2.6, 3.5, 3.16, and 4.15. For additional discussion regarding the Request,

see infra

section I.B.5

See, e.g.,

Feedback Flyer Response of Tomas Liutvinas on S7-10-21 (Aug. 28, 2021) (“It seems like there is no conflict of interest regulations in the US financial system. This makes me uneasy. Until the rights are fully explained, reported, and undone I will recommend to anyone I know to stay away from US markets. For myself, I've invested in a certain position with plans to leave the investment for the future generations of my family, to hold on hopefully up to a point when markets will be made transparent and fair.”); Feedback Flyer Response of Jasper Pummell on S7-10-21 (Aug. 28, 2021) (“I believe that online brokerages have a conflict of interest and financial regulation is needed to ensure that the markets are a safe place for retail traders.”); Feedback Flyer Response of Robert on S7-10-21 (Aug. 27, 2021) (“Retail needs a fair and transparent market. There are blantant [sic] conflicts of interest in the market which should be rectified immediately. Failure to do so will have a mass exodus of investors from the US stock market.”).

See also

FINRA AI Report,

supra

note 9, at 11 (“However, use of AI also raises several concerns that may be wide-ranging across various industries as well as some specific to the securities industry. Over the past few years, there have been numerous incidents reported about AI applications that may have been fraudulent, nefarious, discriminatory, or unfair, highlighting the issue of ethics in AI applications.”).

But see, e.g.,

Comment Letter from David Dusseault, President, Robinhood Financial, LLC (Oct. 1, 2021) (“Robinhood Letter”) (stating that conflicts of interest are not new to the financial industry and that the regulatory frameworks established by the SEC, such as Reg BI and the disclosure requirements of the Investment Advisers Act of 1940, rest on the principle that conflicts of interest exist, but investors are able to navigate them when they are adequately disclosed); Comment Letter from Investment Adviser Association (Oct. 1, 2021) (“IAA Letter”); Comment Letter from Kevin M. Carroll, Managing Director and Associate General Counsel, Securities Industry and Financial Markets Association (Oct. 1, 2021) (“SIFMA Letter”) (generally opposing new rules, guidance, or interpretations to address the use of digital engagement practices). These comments are all available in the comment file at

https://www.sec.gov/comments/s7-10-21/s71021.htm.

Failures to appropriately oversee these PDA-like technologies compound the risk that conflicts of interest may not be appropriately identified or managed. Due to the complexity and opacity of certain technologies, firms should have robust practices to appropriately oversee and understand their use and take steps to identify and appropriately address any associated conflicts of interest. For example, without appropriate personnel, a firm may not have the ability to modify the software or may lack the expertise to understand, monitor, or appropriately update code, limiting the firm's ability to identify and appropriately address associated conflicts of interest. Furthermore, if the firm does not understand how the technology operates—including whether it takes into consideration the firm's interest and how it can influence investor conduct—the firm may not fully understand whether, how, or the extent to which it is placing the firm's interests ahead of investors' interests. As a result of the complexity and opacity of PDA-like technologies, a firm needs different and specific practices to evaluate its use of the technology and recognize the risk of conflicts presented by that use compared to other practices. Without appropriate oversight and understanding of the conflicts of interest that could be amplified when the technology is incorporated into investor-facing interactions, such as design elements, features, or communications that nudge or prompt certain or more immediate action by an investor, investor harm can result.

5. Request for Information and Comment

In August 2021, the Commission issued a request for information and public comment on the use of DEPs by broker-dealers and investment advisers, as well as the analytical and technological tools and methods used in connection with these DEPs.

For purposes of the Request, the Commission defined DEPs broadly to include behavioral prompts, differential marketing, game-like features, and other design elements or features designed to engage retail investors.

The Commission stated that DEPs may be designed to encourage account opening, account funding and trading, or may be designed solely to increase investor engagement with investing apps, as there may be value in the number of investors interacting with the platform, how often they visit, and how long they stay.

The Request was issued in part to assist the Commission and its staff in better understanding the market practices associated with the use of DEPs by firms, facilitate an assessment of existing regulations and consideration of whether regulatory action may be needed to further the Commission's mission in connection with firms' use of DEPs, as well as to provide a forum for market participants (including investors), and other interested parties to share their perspectives on the use of DEPs and the related tools and methods, including potential benefits that DEPs provide to retail investors, as well as potential investor protection concerns.

See

Request,

supra

note 90.

See id.

at 49067.

See id.

at 49069.

As noted in the Request, the market practices explored included: (i) the extent to which firms use DEPs; (ii) the types of DEPs most frequently used; (iii) the tools and methods used to develop and implement DEPs; and (iv) information pertaining to retail investor engagement with DEPs, including any data related to investor demographics, trading behaviors, and investment performance.

See id.

at 49068.

The Commission received over 2,300 public comments, including submissions provided through an online “feedback flyer” that accompanied the Request and was provided to better facilitate responses from retail investors.

Commenters offered a wide range of perspectives on broker-dealers' and investment advisers' use of DEPs, addressing their purpose, providing information on how investors interact with them, and offering broad reflections on potential regulatory action. Commenters also provided views on benefits and risks related to firms' use of DEPs, as well as the AI/machine learning and behavioral psychology that firms use to develop and deploy DEPs.

The “Feedback Flyer” was attached as Appendix A to the Request and asked individual investors to provide their comments with regard to online trading or investment platforms, such as websites and mobile applications, to provide the Commission with a better understanding of retail investors' experiences on these platforms. The Feedback Flyer provided 11 different question prompts, with an array of both multiple choice, and free text response options whereby respondents could submit relevant comments. Comments received in response to the Request are available at

https://www.sec.gov/comments/s7-10-21/s71021.htm.

See, e.g.,

Comment Letter from American Securities Association (Sept. 30, 2021); Comment Letter from Securities Arbitration Clinic and Professor of Clinical Legal Education, St. John's University School of Law Securities Arbitration Clinic, (Oct. 1, 2021) (“St. John's Letter”); Comment Letter from Morningstar, Inc. and Morningstar Investment Management, LLC (Oct. 1, 2021) (“Morningstar Letter”); Comment Letter from James F. Tierney, Assistant Professor of Law, University of Nebraska College of Law (Oct. 1, 2021) (“Tierney Letter”); Pace University Letter; Comment Letter from Law Office of Simon Kogan, (Oct. 17, 2021) (“Kogan Letter”).

A number of commenters also provided detailed feedback regarding the potential need for additional action to address the issues presented by DEPs and their underlying technology. For example, multiple commenters raised concerns over the risks of harm to investors if the Commission did not act, and requested that the Commission interpret existing regulations in a way

that would apply to most DEPs and/or adopt additional regulations to address those risks.

Many of these commenters suggested a need to address the standards of conduct applicable to broker-dealers and investment advisers when interacting with retail investors through digital platforms.

100

Some of these commenters noted that Reg BI does not apply to firms with a self-directed brokerage business model, including those that use DEPs

101

and provided additional suggestions that the Commission could take to address firms' use of DEPs.

102

Others provided detailed opinions as to the application of an investment adviser's fiduciary duty to DEPs.

103

A significant number of commenters also addressed other laws and regulations and their sufficiency, or lack thereof, in their application to DEPs, including discussion addressing (i) antifraud and general standards of conduct;

104

(ii) regulation of advertising, marketing, and communications with the public;

105

(iii) compliance and supervision obligations;

106

(iv) data privacy and cybersecurity concerns;

107

(v) customer onboarding obligations;

108

(vi) Commission Staff's 2017 Robo-Adviser Guidance;

109

and (vii) the Advisers Act recordkeeping rule.

110

See, e.g.,

Comment Letter from Scopus Financial Group (Sept. 20, 2021); Comment Letter from Better Markets, Inc. (Oct. 1, 2021) (“Better Markets Letter”); Comment Letter from Public Investors Advocate Bar Association (Oct. 1, 2021) (“PIABA Letter”); Comment Letter from University of Miami School of Law Investor Rights Clinic et al. (Oct 1, 2021) (“University of Miami Letter”); Comment Letter from Fidelity Investments (Oct. 1, 2021); St. John's Letter; Morningstar Letter. We also considered views received from the SEC's Investor Advisory Committee on ethical guidelines for artificial intelligence and algorithmic models used by investment advisers.

See

Investor Advisory Committee, Establishment of an Ethical Artificial Intelligence Framework for Investment Advisors (Apr. 6, 2023),

https://www.sec.gov/files/20230406-iac-letter-ethical-ai.pdf

100

See, e.g.,

Pace University Letter (“We believe that retail investors, particularly novice investors, believe that they are receiving advice or recommendations from DEPs. This includes the top mover list, analyst ratings, push notifications, and other DEPs that encourage investment activity. Many of our survey participants stated that they believe that these DEPs influenced their decision-making. At the same time, DEPs may also influence investor decision-making without investors being conscious of it.”); Comment Letter from North American Securities Administrators Association (Oct. 1, 2021) (“NASAA Letter”) (“To assist with compliance and to protect investors, the Commission should provide further guidance as to when DEP-based communications constitute recommendations. However, given the speed of technology, NASAA suggests that guidance should not be limited to any particular DEP, but rather should be focused on the effects of technologies on investor behavior generally.”); Comment Letter from Fiduciary Insights and Practice Growth Partners (Sept. 30, 2021) (“Aikin/Mindicino Letter”) (“[A]s the complexity and heterogeneity of wants, needs, and capabilities of the clientele rises, the sophistication and artificial intelligence and machine learning (AI/ML) of the DEPs must increase dramatically. Commensurately, the internal oversight and regulatory guardrails to assure that customer/client best interests are served must also increase.”);

see also

Comment Letter from Morgan Stanley Wealth Management (Oct. 1, 2021) (“Morgan Stanley Letter”) (while noting existing protections, stating that “[s]hould the Commission believe additional guidance is necessary, we suggest the adoption of principles-based, technology neutral adjustments to the existing regulatory regime to address the fast evolving technological landscape”); Better Markets Letter; University of Miami Letter (“As the SEC continues its review of standards applicable to financial professional[s], it is critical to enhance investor protection in the fast-growing and increasingly harmful digital platform environment.”).

101

See, e.g.,

Robinhood Letter (“The SEC acknowledged the benefits of a self-directed model such as Robinhood's in adopting Reg BI, explicitly stating that Reg BI does not apply to this model.”).

102

See, e.g.,

Pace University Letter (“DEPs and online platforms have expanded access to the market to new investors, while at the same time influencing the decision-making of those investors—particularly novice investors—in ways that are often in conflict with their bests interest.”);

see also

Tierney Letter; Better Markets Letter; SIFMA Letter; Morningstar Letter; Morgan Stanley Letter; University of Miami Letter (“Due to the influential nature of DEPs, the SEC should enhance the Regulation Best Interest disclosure obligation and conflict of interest obligation by requiring firms to flag investor trades and/or positions where there is a likelihood that the firm will act in a manner adverse to the investor's position and to notify investors of these potential actions.”).

103

See, e.g.,

IAA Letter (“Some advisers also use various analytical and technological tools to develop and provide investment advice, including through online platforms or as part of enhancing their in-person investment advisory services. Investment advisers may also engage in DEPs to develop and provide investor education and related tools.”);

see also

Comment Letter from Envestnet Asset Management, Inc. (Oct. 1, 2021) (“Envestnet Letter”); Comment Letter from Julius Leiman-Carbia, Chief Legal Officer, Wealthfront Corporation (Oct. 8, 2021) (“Wealthfront Letter”); NASAA Letter; Aikin/Mindicino Letter; Better Markets Letter; SIFMA Letter; University of Miami Letter; Morgan Stanley Letter.

104

See, e.g.,

Comment Letter from Jennifer Schulp, Director of Financial Regulation Studies, Center for Monetary and Financial Alternatives, CATO Institute (Oct. 1, 2021) (“CATO Institute Letter”); Comment Letter from Brandon Krieg, CEO, Stash Financial, Inc. and Stash Investments LLC (Oct. 1, 2021) (“Stash Letter”); Wealthfront Letter; IAA Letter; Robinhood Letter; SIFMA Letter; Tierney Letter.

105

See, e.g.,

PIABA Letter; CATO Institute Letter; IAA Letter.

106

See, e.g.,

Comment Letter from James J. Angel, Ph.D., CFP, CFA, Associate Professor of Finance, McDonough School of Business, Georgetown University (Sept. 30, 2021); IAA Letter; Stash Letter; Aikin/Mindicino Letter; PIABA Letter; CATO Institute Letter.

107

See, e.g.,

NASAA Letter; Envestnet Letter; Kogan Letter.

108

See, e.g.,

University of Miami Letter.

109

See, e.g.,

Comment Letter from Penny Lee, CEO, Financial Technology Association (Oct. 1, 2021); IAA Letter.

110

See, e.g.,

Comment Letter from Pamela Lewis Marlborough, Managing Director and Associate General Counsel, Teachers Insurance and Annuity Association of America (Oct. 1, 2021); SIFMA Letter; University of Miami Letter.

C. Overview of the Proposal

In view of Commission staff observations, our experience administering our existing rules, the discussion in section 1.B. above on the development of PDA-like technologies in firm investor interactions and the unique risks they raise regarding conflicts of interest, and comments received in response to the Request, we are proposing to update the regulatory framework to help ensure that firms are appropriately addressing conflicts of interest associated with the use of PDA-like technologies. Specifically, we propose that firms should be required to identify and eliminate, or neutralize the effect of, certain conflicts of interest associated with their use of PDA-like technologies because the effects of these conflicts of interest are contrary to the public interest and the protection of investors.

111

See infra

section II.A.2.e.

Proposed rules 15l-2 under the Exchange Act (17 CFR 240.15l-2) and 211(h)(2)-4 under the Advisers Act (17 CFR 275.211(h)(2)-4) (collectively, the “proposed conflicts rules”) are designed to address the conflicts of interest associated with firms' use of PDA-like technology when engaging in certain investor interactions, and the proposed rules would do so in a way that aligns with (and in some respects may satisfy) firms' existing regulatory obligations.

112

Except as specifically noted, the texts of proposed conflicts rule applicable to brokers and dealers (17 CFR 240.15l-2) and the proposed conflicts rule applicable to investment advisers (17 CFR 275.211(h)(2)-4) would be substantially identical.

113

The proposed conflicts rules would only apply where the firm uses defined covered technology—more specifically, an analytical, technological, or computational function, algorithm, model, correlation matrix, or similar method or process that optimizes for, predicts, guides, forecasts, or directs investment-related behaviors or outcomes in an investor interaction.

112

See id.

113

Citations herein to the “proposed conflicts rules” reference each of the proposed conflicts rules as they would be codified in each location. Citations to a particular section of the CFR reference only the proposed conflicts rule that would apply to broker-dealers or to investment advisers, as applicable.

The proposal is designed to be sufficiently broad and principles-based to continue to be applicable as technology develops and to provide firms with flexibility to develop approaches to their use of technology consistent with their business model, subject to the over-arching requirement

that they need to be sufficient to prevent the firm from placing its interests ahead of investor interests. The proposal is also designed to be consistent with the Commission's prior actions regarding technological innovation.

114

We note that the staff has also provided their views on the industry's expanding use of technology in the context of robo-advisers

115

and shared examination findings and risks associated with the use of robo-advisory products,

116

among other areas.

114

Historically, the Commission has reviewed the changing technology landscape, provided guidance, and if necessary amended its regulatory framework to protect investors while still allowing firms' use of technology to innovate and benefit investors.

See, e.g.,

Use of Electronic Media for Delivery Purposes, Release No. 7233 (Oct. 6, 1995) [60 FR 53458 (Oct. 10, 1995] (providing Commission views with respect to the use of electronic media for information delivery under the Securities Act of 1933, the Securities Exchange Act of 1934, and the Investment Company Act of 1940); Use of Electronic Media by Broker-Dealers, Transfer Agents, and Investment Advisers for Delivery of Information, Exchange Act Release No. 37182 (May 9, 1996) [61 FR 24644 (May 15, 1996)] (“1996 Release”) (providing Commission views on electronic delivery of required information by broker-dealers, transfer agents and investment advisers); and Use of Electronic Media, Exchange Act Release No. 42728 (Apr. 28, 2000) [65 FR 25843 (May 4, 2000)] (“2000 Release”) (providing interpretive guidance on the use of electronic media to deliver documents on matters such as telephonic and global consent; issuer liability for website content; and legal principles that should be considered in conducting online offerings). In addition, the Commission has amended regulations to accommodate evolving technologies and changes in the way investors consume information.

See, e.g.,

Tailored Shareholder Reports for Mutual Funds and Exchange-Traded Funds; Fee Information in Investment Company Advertisements, Investment Company Act Release No. 34731 (Oct. 26, 2022) (87 FR 72758 [Nov. 25, 2022]) (requiring layered disclosure for funds' shareholder reports and graphical representations of fund holdings); Investment Adviser Marketing, Investment Advisers Act Release No. 5653 (Dec. 22, 2020) [86 FR 13024 (Mar. 5, 2021)] (adopting “principles-based provisions designed to accommodate the continual evolution and interplay of technology and advice,” and providing specific guidance regarding, among others, the use of social media). Further, the Commission has amended regulations to expand the use of electronic filing options by investment advisers and institutional investment managers and updated recordkeeping requirements to make them adaptable to new technologies in electronic recordkeeping.

See, e.g.,

Electronic Submission of Applications for Orders under the Advisers Act and the Investment Company Act, Confidential Treatment Requests for Filings on Form 13F, and Form ADV-NR; Amendments to Form 13F, Advisers Act Release No. 6056 (June 23, 2022) [87 FR 38943 (June 30, 2022)];

see also

Electronic Recordkeeping Requirements for Broker-Dealers, Security-Based Swap Dealers, and Major Security-Based Swap Participants, Exchange Act Release No. 96034 (Oct. 12, 2022) [87 FR 66412 (Nov. 3, 2022)] (“Electronic Recordkeeping Release”).

115

See

Robo-Advisers, Division of Investment Management Guidance Update No. 2017-02 (Feb. 2017) (“2017 IM Guidance”),

https://www.sec.gov/investment/im-guidance-2017-02.pdf

(addressing among other things, presentation of disclosures, provision of suitable advice, and effective compliance programs).

116

See

Observations from Examinations of Advisers that Provide Electronic Investment Advice, Division of Examinations Risk Alert (Nov. 9, 2021) (“2021 Risk Alert”),

https://www.sec.gov/files/exams-eia-risk-alert.pdf

(noting, “[n]early all of the examined advisers received a deficiency letter, with observations most often noted in the areas of: (1) compliance programs, including policies, procedures, and testing.”).

The proposal draws upon our authority under section 211(h) of the Advisers Act and section 15(l) of the Exchange Act. The Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010 (“Dodd-Frank Act”) added section 211(h)(2) to the Advisers Act and section 15(l)(2) to the Exchange Act, each of which, among other things, authorizes the Commission to “promulgate rules prohibiting or restricting certain sales practices, conflicts of interest, and compensation schemes for brokers, dealers, and investment advisers that the Commission deems contrary to the public interest and the protection of investors.”

117

See

Section 913 of the Dodd-Frank Wall Street Reform and Consumer Protection Act, Pub. L. 111-203, 124 Stat. 1376 (2010). As noted in note 8 to subsection (l), another subsection (l) is set out after the first subsection (k) of the Exchange Act.

The proposal is intended to be technology neutral. We are not seeking to identify which technologies a firm should or should not use. Rather, the proposal builds off existing legal standards and, as discussed throughout the release, is designed to address certain risks to investors associated with firms' use of certain technology in their interactions with investors, regardless of which such technology is used.

118

The proposal also is designed to permit firms the ability to employ tools that they believe would address these risks that are specific to the particular technology they use consistent with the proposal. The Commission has long acted to protect investors from the harms arising from conflicts of interests and will continually assess the harms and revise those protections in light of the evolution of practices, including with regard to firms' use of technologies. As discussed in further detail below, conflicts associated with the use of PDA-like technologies should be eliminated or their effects neutralized to protect investors from conflicts of interest associated with firms' use of PDA-like technologies that results in investor interactions that place the interests of the firm and its associated persons ahead of investors' interests.

118

Firms' use of PDA-like technology may also be subject to other potential legal and contractual restrictions on the ability for advisers and brokers to collect and use customer information.

See, e.g.,

17 CFR part 248, subpart A (Regulation S-P), requiring, among other things, brokers, dealers, investment companies, and registered investment advisers to adopt written policies and procedures for administrative, technical, and physical safeguards to protect customer records and information.

In particular, the proposed conflicts rules would generally require the following:

•

Elimination, or neutralization of effect of, conflicts of interest.

The proposed conflicts rules would require a firm to (i) evaluate any use or reasonably foreseeable potential use by the firm or its associated person

119

of a covered technology in any investor interaction to identify any conflict of interest associated with that use or potential use;

120

(ii) determine whether any such conflict of interest places or results in placing the firm's or its associated person's interest ahead of the interest of investors; and (iii) eliminate, or neutralize the effect of, those conflicts of interest that place the firm's or its associated person's interest ahead of the interest of investors.

119

As used in this release, the term “associated person” means, for investment advisers, a natural person who is a “person associated with an investment adviser” as defined in section 202(a)(17) of the Advisers Act and, for broker-dealers, a natural person who is an “associated person of a broker or dealer” as defined in section 3(a)(18) of the Exchange Act.

120

Covered technology, conflict of interest, investor interaction are each defined terms under the proposed rules.

See

proposed rules 211(h)(2)-4(a) and 15l-2(a);

See also

Bob Veres and Joel Bruckstein,

T3/Inside Information Advisor Software Survey

(Mar. 14, 2023),

https://t3technologyhub.com/wp-content/uploads/2023/03/2023-T3-and-Inside-Information-Software-Survey.pdf

124

The SEC has proposed a new rule under the Advisers Act to prohibit registered investment advisers from outsourcing certain services or functions without first meeting minimum requirements.

See

Outsourcing by Investment Advisers, Investment Advisers Act Release No. 6176; File No. S7-25-22 (Oct. 26, 2022) [87 FR 68816 (Nov. 16, 2022)] (“Proposed Outsourcing Rule”). We encourage commenters to review that proposal to determine whether it might affect comments on this proposal.

The proposed definition, however, would be limited to those technologies that optimize for, predict, guide, forecast, or direct investment-related behaviors or outcomes. The use of these terms in the proposed conflicts rules is designed to capture a broad range of actions. This could include providing investment advice or recommendations, but it also encompasses design elements, features, or communications that nudge, prompt, cue, solicit, or influence investment-related behaviors or outcomes from investors. Investment-related behavior or outcomes can manifest themselves in many forms in addition to buying, selling, and holding securities, such as an investor making referrals or increasing trading volume and/or frequency. This broad proposed definition is designed to help ensure that, as innovation and technology evolve and firms expand their reliance on technologies to provide services to, and to interact with, investors, our rules remain effective in protecting investors from the harmful impacts of conflicts of interest.

The proposed definition would apply to the use of PDA-like technologies that analyze investors' behaviors (

e.g.,

spending patterns, browsing history on the firm's website, updates on social media) to proactively provide curated research reports on particular investment products, because the use of such technology has been shown to guide or influence investment-related behaviors or outcomes. Similarly, using algorithmic-based tools, such as investment analysis tools, to provide tailored investment recommendations to investors would fall under the proposed definition of covered technology because the use of such tools is directly intended to guide investment-related behavior. As an additional example, a firm's use of a conditional auto-encoder model to predict stock returns would be a covered technology.

125

Similarly, if a firm utilizes a spreadsheet that implements financial modeling tools or calculations, such as correlation matrices, algorithms, or other computational functions, to reflect historical correlations between economic business cycles and the market returns of certain asset classes in order to optimize asset allocation recommendations to investors, the model contained in that spreadsheet would be a covered technology because the use of such financial modeling tool is directly intended to guide investment-related behavior. Likewise, covered technology would include a commercial off-the-shelf NLP technology that a firm may license to draft or revise advertisements guiding or directing investors or prospective investors to use its services.

125

An autoencoder return model is an unsupervised learning method that attempts to model a full panel of asset returns using only the returns themselves as inputs.

See generally

S. Gu, B. Kelly, and D. Xiu,

Autoencoder Asset Pricing Models

(Sept. 30, 2019),

https://www.aqr.com/Insights/Research/Working-Paper/Autoencoder-Asset-Pricing-Models

The proposed definition, however, would not include technologies that are designed purely to inform investors, such as a website that describes the investor's current account balance and past performance but does not, for example, optimize for or predict future results, or otherwise guide or direct any investment-related action. Similarly, the proposed definition also would not include a technology that predicts whether an investor would be approved for a particular credit card issued by the firm's affiliate based on other

information the firm knows about the investor because the use of such technology does not, and is not intended to, affect an investment-related behavior or outcome. For the same reason, the use of a firm's chatbot that employs PDA-like technology to assist investors with basic customer service support (

e.g.,

password resets or disputing fraudulent account activity) would not qualify as covered technology under the proposed definition.

We request comment on all aspects of the definition of covered technology, including the following items:

1. Is the scope of the proposed definition of a covered technology sufficiently clear? We intend for the proposed definition to cover PDA-like technologies; are there ways we could revise the proposed definition in order to better accomplish this? Are there any technologies covered by the proposed definition that go beyond PDA-like technologies and should be excluded? For instance, should the proposed definition distinguish between different categories of machine learning algorithms, such as deep learning, supervised learning, unsupervised learning, and reinforcement learning processes? Do one or more of these categories present more investor protection concerns related to conflicts of interest relative to other categories? Would firms be able to identify what would and would not be a covered technology for purposes of the proposed rules? If not, what additional clarity would be beneficial? We have described examples of technologies to which the definition would or would not apply. Should the definition be revised to include or specifically exclude such examples?

2. Would the definition adequately include the technology used by firms that would present the conflicts of interest and resulting risks to investors that these proposed rules are designed to address? If not, how should this definition be changed to further the objective of the proposed conflicts rules? Please explain your answer, including the extent to which these technologies do or do not present conflicts of interest risks to investors. Alternatively, do the technologies included in the proposed definition include technology that does not typically result in risks to investors that these proposed rules are designed to address?

3. Is the proposed definition of covered technology appropriately calibrated to allow for future technological developments? What adjustments, if any, should the Commission make to help ensure that the definition of covered technology will remain evergreen despite future technological advancements? Conversely, what adjustments to the definition of covered technology, if any, are necessary to avoid covering those future technological advancements that do not possess characteristics that the proposed rules are intended to address?

4. The proposed definition of covered technology only applies to technologies that are used to optimize for, predict, guide, forecast, or direct investment-related behaviors or outcomes. Do the terms “optimize for,” “predict,” “guide,” “forecast,” and “direct” appropriately scope the definition? Is it clear what these terms are intended to capture or would further explanation be helpful? Are there certain technologies that would fit within one or more of those terms but which should be outside the scope of the proposed definition? Alternatively, are there certain technologies that would fall outside those terms but which should be within the scope of the proposed definition? If so, should we use additional or different words to clarify the meaning? For instance, should we include the term “influence” in the definition? If so, how would “influence” differ from the terms “guide” or “direct” in the definition? Should we use “nudge” or “prompt” in the definition? Alternatively, should we remove any of the terms in the proposed definition? For instance, are the terms “guide” and “direct” redundant or do they express distinct meanings within the context of the definition? Does “guide” capture broader activity than “direct” and cause the rule to capture technologies that should not be in scope? Should the definition be limited to technologies that direct or influence an investor?

5. Should the proposed definition of covered technology apply to technologies that are used to optimize for, predict, guide, forecast, or direct investment-related behaviors or outcomes,

directly or indirectly?

Are there certain PDA-like technologies that optimize for, predict, guide, forecast, or direct investment-related behaviors or outcomes

indirectly

that should be covered by this definition? If so, what are they and why? If the definition did include the term “indirectly,” would it include technologies that should not be covered by the proposed conflicts rules?

6. Should the definition of covered technology not include technology that is solely meant to inform investors, as proposed?

7. Does the term “covered technology” adequately reflect the definition? Should some other defined term be used, such as “covered processes” or “covered methods”? Are there any other terms that should be used?

8. Does the phrase “investment-related behaviors or outcomes” sufficiently clarify the intended scope of the rule and which technologies would not be within the definition? Is it clear what the phrase “investment-related behaviors or outcomes” would capture or would further explanation be helpful? Are there certain behaviors or outcomes that may not be “investment related” but should nonetheless be covered by the proposed definition? For instance, should PDA-like technologies used for back office or administrative functions, such as trade settlement, the routing of customers' orders, accounting, or document review and processing, be included in the covered technology definition? Are commenters aware of any PDA-like technology that is used for back office functions, such as the routing of customer orders, that is also used to engage or communicate with investors (

i.e.,

that involve an investor interaction)? Are there certain investment-related activities that may not be “behaviors or outcomes” that should be covered by the definition? Is either “behavior” or “outcome” overbroad, capturing activities beyond those intended by the definition? Should a different term, such as “investment-related covered technology” be used?

9. Are there aspects of this definition that should be broadened, narrowed, revised, removed, or added? For instance, should the definition be limited to the use of predictive data analytics and/or artificial intelligence that optimizes for, predicts, guides, forecasts, or directs investment-related behaviors or outcomes? Alternatively, should we limit the scope of the definition to technologies that are used to provide investment advice or recommendations? Should we otherwise limit the scope to technologies that are used directly by investors? Should we expressly exclude technologies that are not used by investors but instead are used by individuals who are associated with a firm and use the technologies in communicating with investors?

b. Investor Interaction

The proposed conflicts rules include definitions for both “investor” and “investor interaction.”

126

For brokers or dealers, the definition of investor would include a natural person, or the legal representative of such natural person, who seeks to receive or receives services primarily for personal, family or

household purposes. The definition is designed to capture both prospective and current retail investors.

127

For investment advisers, the definition of investor would include a client or prospective client, and any current or prospective investor in a pooled investment vehicle advised by the investment adviser.

128

The use of PDA-like technology by investment advisers of pooled investment vehicles, such as algorithmically targeted advertisements that are designed to solicit investors in a pooled investment vehicle or algorithmically designed investment strategies in pooled investment vehicles, present the same investor protection concerns as advisers that use the same or similar technology to target or advise their advisory clients. Accordingly, we are proposing to define “investor” so that the proposed conflicts rules would broadly apply both to clients that receive investment advisory services from an investment adviser and to investors in a pooled investment vehicle advised by the investment adviser.

129

126

See

proposed conflict rules at (a).

127

See supra

note 6. Broker-dealers are subject to regulation under the Exchange Act and SRO rules, including a number of obligations that attach when a broker-dealer offers services to a retail customer, including making recommendations, as well as general and specific requirements aimed at addressing certain conflicts of interest. The application of these obligations can vary depending on a broker-dealer's business lines and activities, as well as the level of customer sophistication.

See

Regulation Best Interest, Exchange Act Release No. 83062 (May 9, 2018) [83 FR 21574 (May 9, 2018)], at 21575 (“Reg BI Proposing Release”);

see, e.g.,

FINRA Rule 2210 (applying broker-dealer obligations related to communications with the public differently to communications directed to retail versus institutional investors). Here, the focus of the proposed rules for broker-dealers is on retail investors.

128

See

proposed rule 211(h)(2)-4(a) (specifying that “pooled investment vehicle” has the same meaning as in 17 CFR 275.206(4)-8, meaning any investment company as defined in section 3(a) of the Investment Company Act of 1940 or any company that would be an investment company under section 3(a) of that Investment Company Act but for the exclusion provided from that definition by either section 3(c)(1) or section 3(c)(7) of the Investment Company Act).

129

See

proposed conflict rules at (a) (defining “Investor”).

The proposed conflicts rules would generally define investor interaction as engaging or communicating with an investor, including by exercising discretion with respect to an investor's account; providing information to an investor; or soliciting an investor.

130

This definition would capture a firm's correspondence, dissemination, or conveyance of information to or solicitation of investors, in any form, including communications that take place in-person, on websites; via smartphones, computer applications, chatbots, email messages, and text messages; and other online or digital tools or platforms. This definition would include engagement between a firm and an investor's account, on a discretionary or non-discretionary basis. This definition would also capture any advertisements, disseminated by or on behalf of a firm, that offer or promote services or that seek to obtain or retain one or more investors. The proposed definition is intended to be sufficiently broad to encompass the wide variety of methods, using current and future technologies, that firms could use to interact with investors.

131

130

See

proposed conflict rules at (a).

131

See generally

Investment Adviser Marketing Release,

supra

note 19 (a recent Commission rule designed to accommodate the continual evolution of the use of technology in the investment adviser industry as it relates to advisers marketing their services to clients and investors).

The proposed definition is generally designed to limit the proposed conflicts rules' scope to a firm's use of covered technology in interactions with investors. This aspect of the proposed conflicts rules recognizes that the conflicts associated with the use of covered technology in investor interactions present a higher risk of harm to investors than conflicts associated with technologies that are not used in such interactions. For instance, a firm could utilize covered technology to analyze historical data and current market data to identify trends and make predictions related to the firm's intra-day liquidity needs, peak liquidity demands, and working capital requirements. A firm could likewise use covered technology to make investment decisions about its own assets. Similarly, a firm could implement covered technology for automation of, for example, “back office” processes like the routing of customers' orders

132

and accounting and trade settlement. In each of these examples, the use of covered technology for these processes does not involve an investor interaction, and therefore would not be subject to the proposed conflicts rules.

132

Although routing of customers' orders is not covered by this proposal, broker-dealers owe their customers a duty of “best execution.” Best execution requires that a broker-dealer seek to obtain for its customer orders the most favorable terms reasonably available in the market under the circumstances.

See, e.g., Newton

Merrill, Lynch, Pierce, Fenner & Smith,

135 F.3d 266, 270 (3d Cir. 1998).

see also

FINRA Rule 5310 (Best Execution and Interpositioning). The Commission recently proposed a rule that, if adopted, would establish through Commission rule a best execution standard for broker-dealers.

See

Regulation Best Execution, Exchange Act Release No. 96496 (Dec. 14, 2022) [88 FR 5440 (Jan. 27, 2023)].

In contrast, when a firm's use or potential use of a covered technology in any investor interaction could involve a conflict of interest, a firm would be subject to the framework of the proposed conflicts rules. The proposed definition of investor interaction does not make any distinctions based on the manner in which an investor or the investor's account interacts with the covered technology or on the manner in which the firm uses the technology in the interaction. Meaning, “use” of covered technology in an investor interaction can occur directly through the use of a covered technology itself (

e.g.,

a behavioral feature on an online or digital platform that is meant to prompt, or has the effect of prompting, investors' investment-related behaviors) or indirectly by firm personnel using the covered technology and communicating the resulting information gleaned to an investor (

e.g.,

an email from a broker recommending an investment product when the broker used PDA-like technology to generate the recommendation).

133

To the extent a broker-dealer uses PDA-like technology to make a recommendation to a retail customer, the broker-dealer would also be subject to Reg BI and its attendant obligations, including the Conflict of Interest Obligation, as to the recommendation. Similarly, an investment adviser making a recommendation to its client would also be subject to fiduciary obligations that include a duty of loyalty under which an adviser must eliminate or make full and fair disclosure of all conflicts of interest.

See

Fiduciary Interpretation,

supra

note 8.

Unlike a purely ministerial or back office function, these examples involve an investment-related communication with an investor and would be considered an investor interaction under the proposed definition. Similarly, a firm may use covered technology to provide individual brokers or advisers with customized insights into an investor's needs and interests and the broker or adviser may use this information to supplement their existing knowledge and expertise when making a suggestion to the investor during an in-person meeting. Such a scenario would result in the firm using a covered technology in an investor interaction under the proposed rules. An investor interaction would also include firms' use of game-like prompts or marketing that “nudge” investors to take particular investment-related actions on digital platforms. In addition, the investor interaction definition covers solicitations, for example, a firm utilizing covered technology that scrapes public data, which the firm in turn uses to solicit clients through broadcast emails.

134

See infra

section II.A.2.e (acknowledging that although a firm's use of covered technology to solicit investors to open an account falls under the

definition of an investor interaction, it may not involve a conflict of interest that would require elimination or neutralization under the proposed conflicts rules). On the other hand, a conflict of interest may appear if a firm's chatbot is programmed to solicit only investors that scraped data show are heavy gamblers, and thus perceived as being more profitable to the firm as investors that might invest in risky, high-profit investments that earn the firm more money relative to other investments.

The proposed definition of investor interaction would include interactions that have generally been viewed as outside the scope of “recommendations” for broker-dealers.

135

For example, under the proposed definition, an investor interaction could include: firms' use of research pages or “electronic libraries” to provide investors with the ability to obtain or request research reports, news, quotes, and charts from a firm-created website; or firm's use of technologies to generate emails to investors as part of a firm-run email communication subscription that investors can sign up for and customize, and which alerts investors to items such as news affecting the securities in the investor's portfolio or on the investor's “watch list.”

136

Accordingly, the proposed definition would capture firm communications that may not rise to the level of a recommendation, yet are nonetheless designed to, or have the effect of, guiding or directing investors to take an investment-related action.

135

See

NASD Notice to Members 01-23 (Apr. 2001) (Online Suitability—Suitability Rules and Online Communications) (discussing the types of online communications may constitute “recommendations” under the NASD suitability rule); Reg BI Adopting Release,

supra

note 8, at section II.B.2 (discussing factors to consider when determining whether a “recommendation” has been made by a broker-dealer).

136

See

NASD Notice to Members 01-23,

id.

The proposed definition would exclude from the investor interaction definition interactions solely for purposes of meeting legal or regulatory obligations.

137

These interactions are subject to existing regulatory oversight and/or do not involve the type of conflicts the proposed rules seek to address. This exclusion would apply to interactions with an investor for purposes of obligations under any statute or regulation under Federal or State law, including rules promulgated by regulatory agencies. For example, the proposed definition would exclude interactions with investors solely for anti-money laundering purposes, such as using PDA-like technologies to identify and track investor activity for the purposes of flagging suspected fraudulent transactions and requesting identification and verification of the transaction from an investor (

e.g.,

sending two-factor authentication messages).

138

If a firm, however, includes as part of such an interaction actions that are not reasonably designed to satisfy its obligations under applicable law (

e.g.,

circulating a link to a digital platform that includes features designed to prompt investors to trade along with the annual delivery of Form ADV), and such additional actions are otherwise within the definition of an investor interaction, then such action would be considered an investor interaction for purposes of the proposed conflicts rules.

137

See

proposed conflicts rules at (a).

138

The activities covered under this legal and regulatory obligation exception would qualify as an investor interaction that uses covered technology absent this exception. However, as a practical matter, many of these activities would not involve a firm's use of covered technology under the proposed definition, because such activities would not involve an analytical, technological, or computation function, algorithm, model, correlation matrix, or similar method or process (

e.g.,

delivery of Form ADV or summary prospectus pursuant to legal obligations).

In addition, the proposed definition would also exclude interactions solely for purposes of providing clerical, ministerial, or general administrative support. For example, the proposed definition would exclude basic chatbots or phone trees that firms use to direct customers to the appropriate customer service representative. This aspect of the exclusion is only intended to cover basic or first-level customer support designed to efficiently answer simple questions like providing the business hours of a branch office or the balance in the investor's account, or to guide the investor to a human representative in the appropriate department of the firm who is trained to address the investor's question. On the other hand, if a firm sought to employ a more advanced chatbot designed to answer complex investment-related questions, such as when or whether to invest in a particular investment product or security, this would no longer fit within the exclusion for clerical, ministerial, or general administrative support, and would constitute an investor interaction under the proposed definition.

In either case, the exclusions would be limited to interactions that are “solely for the purpose” of the relevant category (or categories) of conduct in order to help ensure that interactions that serve several purposes, including purposes that are not excluded, will be within the scope of the definition of investor interaction.

139

The “solely for the purpose” language is designed to help ensure that all the functions of a dual-use technology like a chatbot would be considered when evaluating conflicts of interest associated with use of the chatbot.

139

Interactions that are for the purpose of both categories of conduct would also fit within the exclusion. For example, an algorithm whose purpose was both to comply with legal or regulatory obligations

and

to conduct other clerical, ministerial, or general administrative support functions would fit within the exclusion so long as the algorithm did not also have a third purpose that was not excluded from the definition.

We request comment on all aspects of the proposed definitions of investor interaction and investor, including the following items:

10. For broker-dealers, the proposed definition of investor means a natural person, or the legal representative of such natural person, who seeks to receive or receives services from the broker-dealer primarily for personal, family or household purposes. Should we narrow the definition of investor as applied to broker-dealers to only cover retail customers, as defined under Reg BI? Should we expand the definition of investor for brokers or dealers to cover all current and prospective investors and not just retail investors? We have stated that investors may not be able to understand the complexities of covered technologies and any conflicts associated with their use. Should we expand the definition of investor for broker-dealers to cover a certain subset of non-retail investors? The proposed definition of investor for investment advisers is not limited to services “primarily for personal, family or household purposes.” Should we add such limitation in the investment adviser conflicts rule?

11. Should we narrow the definition of investor for investment advisers? For example, should we only apply it to retail investors, as defined in Form CRS? If so, please explain why in comparison to other rules under the Advisers Act.

12. For investment advisers, the proposed definition of investor also includes investors or prospective investors in a pooled investment vehicle that is a client or prospective client of the investment adviser; should we retain this in the final rules? Are there special considerations for investors in a pooled investment vehicle that cause them to need less protection from conflicts of interest associated with a firm's use of covered technology? If the definition of “investor” continues to include investors in pooled investment vehicles, as proposed, are there certain structures or types of pooled investment vehicles that should not be included? For example, should investors in collateralized loan obligation vehicles be excluded? Are there unique characteristics of such vehicles,

investors, or investors in other pooled investment vehicles, which make the additional protections that would be provided by the proposed conflicts rules unnecessary? The proposed definition of “investor” would incorporate the definition of “pooled investment vehicle” in rule 206(4)-8. Should we define the term “pooled investment vehicle” (or use another term)? Should we define the term more broadly for purposes of this rule to include other vehicles to which an investment adviser may provide investment advice that rely on other exclusions from the definition of investment company, such as companies primarily engaged in holding mortgages that are excluded pursuant to section 3(c)(5)(C) of the Investment Company Act, or collective investment trust funds or separate accounts excluded under section 3(c)(11) of the Investment Company Act?

13. Will the proposed definition of investors present challenges for firms that are dually registered as investment advisers and broker dealers?

14. Should we define “prospective investor” in the proposed rules? If so, how should we define this term and why? For example, should we define “prospective investor” as any person or entity that engages in some way with a firm's services (

e.g.,

downloads the firm's mobile app, visits the firm's website, or creates a log-in)? If not, should we provide guidance regarding how firms can identify prospective investors?

15. Is the proposed definition of investor interaction sufficiently clear? Would firms be able to identify what would be an investor interaction for purposes of the proposed conflicts rules? Are there activities that are not covered by the proposed definition of investor interaction that should be? Are there activities that are covered by the proposed definition that should not be? For instance, should a firm soliciting prospective investors be included within the definition? Should the proposed definition be limited to interactions in which investors directly interact with, or otherwise directly use, covered technology? Do situations in which investors do not directly interact with covered technology raise the same concerns of scalability as those in which investors do interact directly?

16. Do commenters agree that investor interactions, as proposed, may entail conflicts of interest that are particularly likely to result in investor harm or to take additional effort to discern? Are there types of activities we should specifically include or exclude within the definition?

17. Do commenters agree that the definition of investor interaction should exclude interactions solely for purposes of meeting legal or regulatory obligations or providing clerical, ministerial, or general administrative support? Should we remove any or all aspects of these exclusions from the definition in the final conflicts rules? In the case of interactions solely for the purpose of meeting legal or regulatory obligations, should we broaden or narrow the exclusion? For example, should we take into account legal or regulatory obligations as a result of compliance with foreign law, or with policies, rules, or directives of SROs (including securities exchanges) or other bodies? Generally, would investor interactions that fall under the proposed exclusions employ covered technology (

e.g.,

technologies that optimize for, predict, guide, forecast, or direct investment-related behaviors or outcomes)? If so, how? If not, is the exception for legal or regulatory obligations additive? Is the exclusion for providing clerical, ministerial, or general administrative support sufficiently clear? For instance, is it clear this phrasing would capture trade settlement and the routing of customers' orders or would further explanation be helpful?

18. Do the proposed conflicts rules adequately address how a firm would treat a single covered technology that features functions that are both included and excluded from the investor interaction definition? For instance, a chatbot that is used for both general customer support help (

e.g.,

password resets) and to provide more advanced functions, such as guiding an investor as to when and whether to invest in a particular investment product. Should the proposed conflicts rules treat these dual-purpose covered technologies differently than covered technology used solely for purposes of meeting legal or regulatory obligations or providing clerical, ministerial, or general administrative support?

19. To the extent we retain or expand the exclusions, are there any conditions we should add in order for a firm to be able to rely on particular exclusions? For example, should we require that a firm create and maintain a written record if it relies on an exclusion? Are there other activities that should be excluded? For example, should we provide a more principles-based exclusion for certain activities that the firm affirmatively identifies in writing as low-risk and that are already part of existing compliance programs or subject to other laws, rules, regulations, or policies?

20. As specified in the proposed definition of investor interaction, the definition would include discretionary management of accounts where the engagement is with the investor's account, even if there is no communication or other interaction with investors themselves at the time of trades in their accounts. Should the discretionary management of accounts be included within the definition of investor interaction? Should it be excluded? Do commenters agree that a firm's discretionary management of accounts using covered technologies may entail conflicts of interest that are particularly likely to result in investor harm and are not sufficiently addressed under the current applicable legal framework? Why or why not?

Identification, Determination, and Elimination, or Neutralization of the Effect of, a Conflict of Interest

The proposed conflicts rules would require a firm to eliminate, or neutralize the effect of, certain conflicts of interest associated with the use of a covered technology in investor interactions.

140

The proposed conflicts rules would also require firms to take affirmative steps as a precursor to eliminating or neutralizing the effect of these conflicts. First, a firm would be required to evaluate any use or reasonably foreseeable potential use of a covered technology in any investor interaction to identify whether it involves a conflict of interest, including through testing the technology. Second, a firm would be required to determine if any such conflict of interest results in an investor interaction that places the interest of the firm or an associated person ahead of investors' interests. Third, the proposed conflicts rules would require a firm to take a particular action—elimination or neutralization—to address any conflict of interest the firm determines in step two results in an investor interaction that places its or an associated person's interest ahead of investors' interests.

141

The proposed conflicts rules thus supplement, rather than supplant, existing regulatory obligations related to conflicts of interest, laying out particular steps a firm must take to address conflicts of interest arising specifically from the use of covered technologies in investor interactions.

142

This is because the nature of these technologies (for example due to their inherent complexity and ability to rapidly scale transmission of conflicted actions across a firm's investor base) requires additional steps to address conflicts associated with their use in investor interactions, compared to conflicts of interest more generally.

140

See infra

section II.A.2.e.

141

On the application to interests of associated persons,

see infra

sections II.A.2.c, II.A.2.d, and II.A.2.e, and proposed conflicts rules at (b)(2) and (3).

142

The elimination or neutralization requirement of the proposed rules applies only to a narrower, defined subset of the broader universe of conflicts—those conflicts that a firm determines

actually

place

the interests of the firm or certain associated persons ahead of the interests of investors. This is in contrast to, for example, an investment adviser's fiduciary duty, which encompasses any interest that

might

incline the adviser, consciously or subconsciously, to provide advice that is not disinterested., or similarly in contrast to the broader universe of conflicts covered by Reg BI. Other conflicts of interest that only

might

affect the firm's investor interactions would continue to be subject to these other obligations, as applicable.

a. Evaluation and Identification

The proposed conflicts rules would require a firm to evaluate any use or reasonably foreseeable potential use by the firm or its associated persons of a covered technology in any investor interaction to identify any conflict of interest associated with that use or potential use.

143

This requirement of the proposal, in connection with the requirement to test and periodically retest any covered technology, is designed to help ensure that a firm has a reasonable understanding of whether its use or reasonably foreseeable potential use of the covered technology in investor interactions would be associated with a conflict of interest.

143

See

proposed conflicts rules at (b)(1).

The proposed conflicts rules do not mandate a particular means by which a firm is required to evaluate its particular use or potential use of a covered technology or identify a conflict of interest associated with that use or potential use. Instead, the firm may adopt an approach that is appropriate for its particular use of covered technology, provided that its evaluation approach is sufficient for the firm to identify the conflicts of interest that are associated with how the technology has operated in the past (for example, based on the firm's experience in testing or based on research the firm conducts into other firms' experience deploying the technology) and how it could operate once deployed by the firm. If a technology could be used in a variety of different scenarios, the firm should consider those scenarios in which it intends that the technology be used (and for which it is conducting the identification and evaluation process). It should also consider other scenarios that are reasonably foreseeable unless the firm has taken reasonable steps to prevent use of the technology in scenarios it has not approved (for example, by limiting the personnel who are able to access the technology).

A firm could adopt different approaches for different covered technologies.

144

Such approaches could vary depending on the nature of the covered technologies employed by the firm at the time they are implemented, how the technologies are used, and the firm's plans for future use of those technologies. For example, a firm that only uses simpler covered technologies in investor interactions, such as basic financial models contained in spreadsheets or simple investment algorithms, could take simpler steps to evaluate the technology and identify any conflicts of interest, such as requiring a review of the covered technology to confirm whether it weights outcomes based on factors that are favorable for the adviser or broker-dealer, such as the revenue generated by a particular course of action.

145

Even when a firm identifies a conflict of interest associated with a simple covered technology, depending on the facts and circumstances, it may determine that such conflict of interest does not actually result in the firm's or an associated person's interests being placed ahead of those of investors, and that the conflict of interest does not need to be eliminated or its effects to be neutralized.

144

Cf.

U.S Chamber of Commerce Technology Engagement Center, Report of the Commission on Artificial Intelligence Competitiveness, Inclusion, and Innovation (Mar. 9, 2023), at 82 (“Chamber of Commerce AI Report”),

https://www.uschamber.com/assets/documents/CTEC_AICommission2023_Report_v6.pdf

(calling for “impact assessments” to help categorize potentially harmful uses of certain technologies in a risk-based framework).

145

See infra

section II.A.2.d, discussing financial models.

Firms that use more advanced covered technologies may need to take additional steps to evaluate technology adequately and identify associated conflicts adequately.

146

For example, a firm might instruct firm personnel with sufficient knowledge of both the applicable programming language and the firm's regulatory obligations to review the source code of the technology, review documentation regarding how the technology works, and review the data considered by the covered technology (as well as how it is weighted).

147

A firm seeking to evaluate an especially complex covered technology and identify conflicts of interest associated with its use may consider other methods as well. For example, if a firm is concerned that it may not be possible to determine the specific data points that a covered technology relied on when it reached a particular conclusion, and how it weighted the information, the firm could build “explainability” features into the technology in order to give the model the capacity to explain why it reached a particular outcome, recommendation, or prediction.

148

By reviewing the output of the explainability features, the firm may be able to identify whether use

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