Algorithm Compliance Does Not Happen Automatically

How Regulators See Algorithms

The power of algorithms in both service and value creation is undisputed, but there is another aspect of algorithms, namely, the compliance dimension. Multiple regulatory bodies including the SEC, FINRA, the CFPB, and the FTC have focused on algorithms from within the scope of their requirements and restrictions.

Robo Advisers Under SEC Scrutiny 

Per SEC regulatory guidance, the SEC monitors robo advisers to evaluate how they meet obligations under the Investment Advisers Act of 1940. 

As with any registered investment adviser, robos must meet the substantive and fiduciary obligations of the Advisers Act. These include the presentation of disclosures to clients related to:

• the functioning of the robo and its advisory services as well as any circumstances where its trading decisions are overridden, 

• the obligation to obtain necessary information from clients in order to meet its duty to supply advice in those clients’ best interest, including through intake questionnaires and other partly or fully automated account creation tools; and finally, 

• “the adoption and implementation of effective compliance programs reasonably designed to address particular concerns relevant to providing automated advice,” including design, implementation, and annual review of written policies and procedures that are reasonably designed to prevent violations of the Advisers Act, as well as ongoing review of the algorithmic code and its behaviors. 

FINRA Supervisory Principles

FINRA has provided guidance on effective supervision and control practices for broker-dealers that use algorithmic strategies. 

Their practices are focused on five general areas: 

While each of these is a complex area of its own, with respect to compliance, FINRA’s core principle is to ensure “that there is effective communication between compliance staff and the staff responsible for algorithmic strategy development is a key element of effective policies and procedures.” In other words, algorithms can not be a “black box.” They must be accounted for in the overall compliance strategy and be subject to day-to-day operational monitoring and controls. 

CFPB and Fairness Concerns

The CFPB, with its focus on credit access, credit pricing, and borrowing costs, has expressed concerns about the use of automated, machine learning, or algorithm-based tools to evaluate creditworthiness in alternative lending. 

The Bureau is scrutinizing the use of alternative data and machine learning in these scenarios to ensure compliance with the Equal Credit Opportunity Act (ECOA). While it encourages lenders to develop innovative means of granting access to credit, particularly for people whose credit access has been historically limited, it also expects lenders to maintain “a compliance management program that appropriately identifies and addresses risks of legal violations,” in ways that are appropriate to the data and scoring models being used.

FTC Algorithm Transparency Rules

Finally, the FTC has demonstrated similar concerns about the fairness and transparency of the use of algorithms in both fintech and in other consumer scenarios. 

In a statement published on April 8, 2020, its “law enforcement actions, studies, and guidance emphasize that the use of AI tools should be transparent, explainable, fair, and empirically sound, while fostering accountability.” While the statement is not a regulation per se, it sheds light on the areas the FTC scrutinizes. Because algorithms make decisions that affect the end-user, they potentially violate laws such as the Fair Credit Reporting Act (FCRA) and the Equal Credit Opportunity Act (ECOA) or cause consumer injury with unfair and deceptive practices as a result of algorithmically-determined decisions. With all of their power, algorithms might intentionally or inadvertently include biases that violate FTC principles of fairness.