# Conformed to Federal Register version and consolidated with correction 34-97990A > Briefs, arguments, decisions, and more. URL: https://www.frixlaw.com/law-library/documents/agency%3Asec%3A6c70cbe3d5516319 ## Record - **Collection:** Agency decision - **Document type:** Agency decision ## Text Conformed to Federal Register version and consolidated with correction 34-97990A 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 BrokerDealers 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. A summary of the proposal of not more than 100 words is posted on the Commission’s website (https://www.sec.gov/rules/2023/07/s7-12-23#34-97990). 2 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 Act1 (“proposed rule 240.15l-2”) and 17 CFR 275.211(h)(2)-4 under the Advisers Act2 (“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”). 1 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]. 2 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]. 3 Table of Contents I. Introduction ................................................................................................................ 6 A. Overview ................................................................................................................. 7 B. Background ........................................................................................................... 12 1. Evolution in the Investment Industry and its Technology Use ....................... 12 2. Current PDA-Like Technology Use and Expected Growth ........................... 15 3. Commission Protection of Investors as Technology Has Evolved ................. 21 4. Use of Predictive Data Technologies in Investor Interactions ........................ 27 5. Request for Information and Comment .......................................................... 33 C. Overview of the Proposal...................................................................................... 37 II. Discussion .................................................................................................................. 42 A. Proposed Conflicts Rules ...................................................................................... 42 1. Scope ............................................................................................................... 42 2. Identification, Determination, and Elimination, or Neutralization of the Effect of, a Conflict of Interest .................................................................................. 60 3. Policies and Procedures Requirement ........................................................... 112 B. Proposed Recordkeeping Amendments .............................................................. 135 III. Economic Analysis .................................................................................................. 142 A. Introduction ......................................................................................................... 142 B. Broad Economic Considerations......................................................................... 144 C. Economic Baseline.............................................................................................. 151 1. Affected Parties ............................................................................................. 151 2. Technology and Market Practices ................................................................. 155 3. Regulatory Baseline ...................................................................................... 158 D. Benefits and Costs............................................................................................... 168 1. Benefits ......................................................................................................... 171 2. Costs.............................................................................................................. 182 E. Effects on Efficiency, Competition, and Capital Formation............................... 191 1. Efficiency ...................................................................................................... 191 2. Competition................................................................................................... 193 3. Capital Formation ......................................................................................... 194 F. Reasonable Alternatives...................................................................................... 195 1. Expressly permit, or require, the use of independent third-party analyses. .. 195 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. ............................................................................................. 196 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. .................................... 197 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. .................................... 198 5. Require that firms test covered technologies on an annual basis, or at a specific minimum frequency......................................................................... 199 6. Require that firms provide a prescribed and standardized disclosure. .......... 200 4 G. Request for Comment ......................................................................................... 202 IV. Paperwork Reduction Act...................................................................................... 205 A. Introduction ......................................................................................................... 205 B. Proposed Conflicts Rules and Proposed Recordkeeping Amendments .............. 207 C. Request for Comment ......................................................................................... 212 V. Initial Regulatory Flexibility Analysis .................................................................. 213 A. Reason For and Objectives of the Proposed Action ........................................... 213 1. Proposed Rules 15l-2 and 211(h)(2)-4 .......................................................... 213 2. Proposed Amendments to Rules 17a-3 and 17a-4 and Rule 204-2 .............. 215 B. Legal Basis .......................................................................................................... 216 C. Small Entities Subject to the Rules and Rule Amendments ............................... 217 1. Small Advisers Subject to Proposed Rule 211(h)(2)-4 and Proposed Amendments to Recordkeeping Rule ........................................................... 217 D. Small Broker-Dealers Subject to Proposed Conflicts Rule and Amendments to Recordkeeping Rules .......................................................................................... 218 E. Projected Reporting, Recordkeeping, and Other Compliance Requirements ..... 218 1. Proposed Conflicts Rules .............................................................................. 219 2. Proposed Amendments to Rule 204-2 .......................................................... 220 3. Proposed Amendments to Rules 17a-3 and 17a-4 ........................................ 221 F. Duplicative, Overlapping, or Conflicting Federal Rules .................................... 222 1. Proposed Rule 211(h)(2)-4 and Proposed Amendments to Rule 204-2 ....... 222 2. Proposed rule 15l-2 and proposed amendments to rules 17a-3 and 17a-4 ... 224 G. Significant Alternatives ...................................................................................... 225 H. Solicitation of Comments ................................................................................... 227 VI. Consideration of Impact on The Economy........................................................... 228 Statutory Authority ......................................................................................................... 228 Text of Proposed Rules and Form Amendments ............................................................ 229 5 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.3 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 PDAlike 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.4 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 3 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-ininvestment-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/2023-0421/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-thedesign-society/article/generative-pretrained-transformer-for-design-concept-generation-anexploration/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). 4 See infra section I.C. 6 required under existing regulatory frameworks5 to better protect investors from harms arising from these conflicts. A. Overview Broker-dealers may have a range of conflicts of interest with their retail investors.6 Likewise, investment advisers may have conflicts of interest with respect to advisory clients and investors in their pooled investment vehicle clients.7 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. 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 5 See infra section III.C.3 6 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. 7 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. 7 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.8 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. 8 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. 8 Recently, firms’ adoption and use of PDA-like technologies9 have accelerated.10 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.11 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 9 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-learningexplained. 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/wpcontent/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”). 10 See infra section I.B. 11 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). 9 investor base.12 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 using13 and to oversee conflicts that are created by or transmitted through its use of such technology.14 Moreover, PDA-like technologies may have the capacity to process data, scale outcomes from analysis of data, and evolve at rapid rates.15 While valuable in many circumstances, these technologies could rapidly and exponentially scale the transmission of any conflicts of interest 12 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”). 13 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). 14 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.”). 15 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-humanintelligence/ (“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-themevolve-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.”). 10 associated with such technologies to investors.16 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 drifted17 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. 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.18 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 16 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.”). 17 See infra note 157 and accompanying text. 18 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). 11 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. 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.19 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. 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 19 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”). 12 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.20 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.21 20 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/speechestestimony/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/socialinvesting-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[.]”). 21 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. 13 In recent years, we have observed a rapid expansion in firms’ reliance on technology and technology-based products and services.22 The use of technology is now central to how firms provide their products and services to investors.23 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.24 In addition, existing technologies for data-analytics and data collection continue to improve and find new applications.25 22 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). 23 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/NFCSInvestor-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). 24 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-away-to-let-a-robot-do-it-70a4587b. 25 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/. 14 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.26 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.27 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.28 Firms 26 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). 27 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. 28 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-stockmarket-continue-to-surge.html (providing year-over-year app download statistics for Robinhood, Webull, 15 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)29 for services such as trading, roboadvice, 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.30 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.31 The rate at which PDA-like technologies continues to evolve is increasing32 and firms are exploring and deploying AI-based applications across different functions of their organizations, including customer facing, investment, and operational activities.33 These PDA-like technologies 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/2019-1114/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). 29 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. 30 See, e.g., SEC Investor Bulletin: Robo-Advisers (Feb. 23, 2017), https://www.sec.gov/oiea/investor-alertsbulletins/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). 31 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. 32 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.”). 33 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-roboadvisors-and-chatbots (describing current uses and development) (“FinanceGPT"). 16 are complex and may include several categories of machine learning34 algorithms, such as deep learning,35 supervised learning,36 unsupervised learning,37 and reinforcement learning38 processes.39 In the past few years, these PDA-like technologies have made increasing use of natural language processing and natural language generation.40 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.41 Some of these chatbots have passed what is known as the “Turing test” and have 34 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. 35 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. 36 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. 37 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. 38 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. 39 See also FSB AI Report, supra note 9; Treasury RFI, supra note 9. 40 See, e.g., FINRA AI Report, supra note 9. 41 See Cade Metz, How Smart Are the Robots Getting?, The New York Times (Jan. 20, 2023, updated Jan. 25, 2023). 17 become virtually indistinguishable from humans in particular situations.42 AI use is increasing year over year and in an array of applications.43 For instance, some robo-advisers use chatbots and NLP technology for their online platforms to provide investment advice and manage investment portfolios.44 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. 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.45 Many expect this momentum to continue, with AI becoming a mainstream technology across many industries, including the financial sector.46 Organizations, including firms in the securities industry,47 are using AI in a multitude of ways, including responding to customer inquiries, 42 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. 43 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/. 44 See, e.g., FinanceGPT, supra note 33 (describing current uses and development). 45 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/2023-0421/vanguard-fidelity-experts-explain-how-ai-is-changing-wealth-management (discussing experts views on AI impact on the wealth management industry). 46 Id. 47 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.”). 18 automating back-office processes, quality control,48 risk management, client identification and monitoring, selection of trading algorithms, and portfolio management.49 Others are actively developing investment advisory services based on PDA-like technologies.50 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.51 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.52 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 48 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. 49 IOSCO AI/ML Report, supra note 47. 50 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[.]”). 51 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/201715/n4/ISEDJv15n4p38.html. 52 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-infinance.pdf. 19 formatting to influence trading decisions.53 Some trading apps use PDA and AI/machine learning along with detailed user data to increase user engagement and trading activity.54 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.55 Firms’ nascent use of AI may already be exposing investors to these types of risks as well as others.56 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 PDAlike 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 53 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”). 54 See, e.g., Alex McFarland, 10 “Best” AI Stock Trading Bots, Unite.AI (June 4, 2023), https://www.unite.ai/stock-trading-bots/. 55 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.”). 56 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”). 20 engineering to change investor behavior in a manner that benefits the firm but is to the detriment of the investor. 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.57 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.58 The proposal, thus, is consistent with the Commission’s practice of evolving our regulation in light of market and technological developments. 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 selfregulatory organizations,59 that are designed to promote conduct that, among other things, protects investors, including protecting investors from conflicts of interest.60 To the extent PDA- 57 See supra section I.B.2. 58 See infra note 114. 59 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. 78o(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.” 60 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 21 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;61 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.62 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. The Commission has long acted to protect investors against the harm that can come when a firm acts on its conflicts of interest.63 For example, the Commission has brought enforcement 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). 61 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). 62 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. 63 See infra section III.C. 22 actions regarding an investment adviser’s fiduciary duty to its clients with respect to conflicts of interest.64 Similarly, the Commission has reinforced fraud protection for investors in pooled investment vehicles against conflicts of interest through rule 206(4)-8.65 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.66 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.67 For example, under existing antifraud provisions of the Exchange Act, a 64 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 v. 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 frontrunning 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). 65 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). 66 See 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.”). 67 See infra section III.C.3 23 broker-dealer has a duty to disclose material adverse information to its customers.68 Indeed, the Commission has enforced a broker-dealer’s duty to disclose material conflicts of interest under the antifraud provisions.69 Broker-dealers are subject to specific FINRA rules aimed at addressing certain conflicts of interest.70 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,71 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”).72 68 A broker-dealer may be liable if it does not disclose “material adverse facts of which it is aware.” See, e.g., Chasins v. Smith, Barney & Co., 438 F.2d 1167, 1172 (2nd Cir. 1970); SEC v. 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). 69 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). 70 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. 71 See Reg BI Adopting Release supra note 8, at text accompanying n.21. 72 17 CFR 240.15l-1(a)(2)(iii) (“Exchange Act rule 15l-1(a)(2)(iii)”). 24 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,73 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. 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 73 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-artificialintelligence/ (“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.”). 25 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 testing74—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.75 For 74 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. 75 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?”). 26 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. 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.76 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,77 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,78 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.79 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 76 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”). 77 See FINRA AI Report, supra note 9, at 4. 78 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-ininvestment-management.html. 79 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). 27 interests ahead of investors’ interests and thus harm investors.80 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,81 (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.82 80 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. 81 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, e.g., Feedback Flyer Response of Lincoln Li on S7-10-21 (Aug. 27, 2021) (“I started half a decade ago following value investing practices. However, [online investment and trading apps], that I used for a short time got me into day trading and speculation more frequently. I ended up stopping using these apps because they took up so much time with little gain. I spent more time long term trading based off of proper market factors and evaluation. There’s a big concern to me, especially as a professional game designer, as to how gamification in life impacting subjects can have negative impact on society, culture and personal finances. I have friends who got into technical trading and day trading due to these apps, who talk more like gamblers than actual investors. It sets a very poor precedent for this industry and behavior.”); Feedback Flyer Response of Richard Green on S7-10-21 (Sept. 25, 2021) (responding to a question about online trading and investment platforms: “[m]y broker rewards referrals by offering free stocks for each referral. I think this pulls new investors into trading, which makes a lot of money for the broker, as newer investors are more likely to trade too frequently or make mistakes.”); Feedback Flyer Response of Joseph on S7-10-21 (Aug. 28, 2021) (“[A trading app’s] user interface is set up in a way to subconsciously influence retail traders to trade more frequently and engage in riskier investment products (options) than the average amount.”). 82 In Congressional hearings related to market events in January 2021, investor protection concerns were identified relating to the use of certain types of DEPs, including advertisements targeted towards specific groups of investors on digital platforms and game-like features on mobile apps. See Game Stopped? Who Wins and Loses When Short Sellers, Social Media, and Retail Investors Collide: Hearing Before the H. 28 In some cases, the use of PDA-like technologies to place a firm’s interests ahead of investors’ interests could reflect an intentional design choice.83 In other cases, however, the actions that place a firm’s interests ahead of the interest of investors may instead reflect the firm’s failure to fully understand the effects of its use of PDA-like technologies or to provide appropriate oversight of its use of such technologies.84 For example, AI and other similar technology are only as good as the data upon which it is based. Corrupted or mislabeled data, biased data, or data from unknown sources, can undermine data quality, leading to skewed outcomes with opaque biases as well as unintended failures.85 While the risk of poor data quality or skewed data is not unique to AI, the ability of PDAlike 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 Comm. on Fin. Servs., 113th Cong. (2021), https://financialservices.house.gov/calendar/eventsingle.aspx?EventID=407107; Game Stopped? Who Wins and Loses When Short Sellers, Social Media, and Retail Investors Collide, Part II: Hearing Before the H. Comm. on Fin. Servs., 113th Cong. (2021), https://financialservices.house.gov/calendar/eventsingle.aspx?EventID=406268; Game Stopped? Who Wins and Loses When Short Sellers, Social Media, and Retail Investors Collide, Part III: Hearing Before the H. Comm. on Fin. Servs., 113th Cong. (2021), https://financialservices.house.gov/calendar/eventsingle.aspx?EventID=407748; Who Wins on Wall Street? GameStop, Robinhood, and the State of Retail Investing: Hearing Before the S. Comm. On Banking, Hous., & Urban Affairs, 113th Cong. (2021), https://www.banking.senate.gov/hearings/who-wins-on-wallstreet-gamestop-robinhoodand-the-state-of-retail-investing. 83 See, e.g., Megan Ji, Note, Are Robots Good Fiduciaries? Regulating Robo-Advisors Under the Investment Advisers Act of 1940, 117 COLUM. L. REV. 1543, 1580 (Oct. 2017) (recommending that the Commission adopt regulations in which “robo-advisors, in their disclosures, clearly delineate between conflicts that are programmed into their algorithms and conflicts that may affect the design of algorithms.”). 84 See Catherine Thorbecke, Plagued with errors: A news outlet’s decision to write stories with AI backfires, CNN (Jan. 23, 2023), https://www.cnn.com/2023/01/25/tech/cnet-ai-tool-news-stories/index.html. 85 See e.g., Regulation Systems Compliance and Integrity, Release No. 34-97143 (Mar. 15, 2023) [88 FR 23146 (Apr. 14, 2023)] (describing the potential market impact of a corrupted data security-based swap data repository). 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/190888/5famous-analytics-and-ai-disasters.html. 29 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.86 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,87 giving rise to erroneous or poor predictions, resulting in a failure to achieve the system’s intended objectives,88 and benefiting the firm over investors (whether intentionally or unintentionally). 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 86 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 costeffective. 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. 87 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/. 88 Id. 30 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.89 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”)90 solicited comments related to conflicts of interest, among other areas.91 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.92 89 In re. Charles Schwab & Co., Inc., et al., Exchange Act Release No. 95087 (June 13, 2022) (settled order). 90 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)]. 91 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 92 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 31 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 PDAlike 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 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. 32 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.93 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.94 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.95 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 93 See Request, supra note 90. 94 See id. at 49067. 95 See id. at 49069. 33 methods, including potential benefits that DEPs provide to retail investors, as well as potential investor protection concerns.96 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.97 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.98 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 96 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. 97 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. 98 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”). 34 way that would apply to most DEPs and/or adopt additional regulations to address those risks.99 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 selfdirected brokerage business model, including those that use DEPs101 and provided additional 99 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 DEPbased 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.”). 35 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.110 102 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. 36 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 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, 111 See infra section II.A.2.e. 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. 37 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. 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 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 BrokerDealers, 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”). 38 views on the industry’s expanding use of technology in the context of robo-advisers115 and shared examination findings and risks associated with the use of robo-advisory products,116 among other areas. 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 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 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-riskalert.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.”). 117 See Section 913 of the Dodd-Frank Wall Street Reform and Consumer Protection Act, Pub. L. No. 111203, 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. 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. 39 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. 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 person119 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 infra sections II.A.1 and II.A.2.c. 40 • Policies and procedures. The proposed conflicts rules would require a firm that has any investor interaction using covered technology to adopt, implement, and, in the case of broker-dealers, maintain, written policies and procedures reasonably designed to achieve compliance with the proposed conflicts rules, including (i) a written description of the process for evaluating any use (or reasonably foreseeable potential use) of a covered technology in any investor interaction; (ii) a written description of any material features of any covered technology used in any investor interaction and of any conflicts of interest associated with that use; (iii) a written description of the process for determining whether any conflict of interest identified pursuant to the proposed conflicts rules results in an investor interaction that places the interest of the firm or person associated with the firm ahead of the interests of the investor; (iv) a written description of the process for determining how to eliminate, or neutralize the effect of, any conflicts of interest determined pursuant to the proposed conflicts rules to result in an investor interaction that places the interest of the firm or associated person ahead of the interests of the investor; and (v) a review and written documentation of that review, no less frequently than annually, of the adequacy of the policies and procedures established pursuant to the proposed conflicts rules and the effectiveness of their implementation as well as a review of the written descriptions established pursuant to the proposed conflicts rules. Proposed amendments to applicable recordkeeping rules, rules 17a-3 and 17a-4 under the Exchange Act and rule 204-2 under the Advisers Act, would require firms to make and keep books and records related to the requirements of the proposed conflicts rules. These proposed 41 amendments are designed to help facilitate the Commission’s examination and enforcement capabilities, including assessing compliance with the requirements of the proposed conflicts rules. The proposal is designed to prevent firms’ conflicts of interest from harming investors while allowing continued technological innovation in the industry. II. DISCUSSION A. Proposed Conflicts Rules 1. Scope The proposed conflicts rules would apply only when a firm uses covered technology in an investor interaction. The proposed definitions are designed to identify those conflicts of interest that firms must evaluate to determine whether they result in investor interactions that place the firm’s interest ahead of investors’ interest and must therefore be eliminated or their effect neutralized.121 The proposed conflicts rules would apply to all broker-dealers and to all investment advisers registered, or required to be registered, with the Commission. a. Covered Technology The proposed conflicts rules would define covered technology as 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.122 The proposed definition is designed to capture PDA-like technologies, such as AI, machine learning, or deep learning algorithms, neural networks, NLP, or large language 121 See supra section I.B.4 (describing existing technologies that may involve conflicts of interest) and infra section II.A.2.c (discussing the proposed definition of a conflict of interest). 122 Proposed conflicts rules at (a). 42 models (including generative pre-trained transformers), as well as other technologies that make use of historical or real-time data, lookup tables, or correlation matrices among others. The rate at which these technologies evolve has increased in recent years and may continue to increase.123 Accordingly, the proposed definition of covered technology is also designed to capture the variety of technologies and methods that firms currently use as well as those technologies and methods that may develop over time. The proposed definition would include widely used and bespoke technologies, future and existing technologies, sophisticated and relatively simple technologies, and ones that are both developed or maintained at a firm or licensed from third parties.124 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 investmentrelated 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 123 See e.g., 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-ininvestment-management.html (stating, for example, that “[f]irms have recognized a new opportunity to gain direct distribution to investors, benefit from enhanced efficiencies in servicing small accounts, and offer value-added services for advisors. This has translated into a wave of investment activity, with asset managers and intermediaries acquiring or investing in robo-advice technology.”) 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-SoftwareSurvey.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)] (“Propose [Text truncated at 120,000 characters. The full text is on the page linked above.] --- Source: Frix Law Library, https://www.frixlaw.com/law-library/documents/agency%3Asec%3A6c70cbe3d5516319. Public record. Not legal advice.