"Consumer Compliance Outlook—Fintech, Alternate Data, and Fair Lending Risks"

Written by André B. Cotten, Regulatory  Compliance Counsel

Consumer Compliance Outlook. The Second 2017 Issue of the Philadelphia Federal Reserve's Consumer Compliance Outlook is now available. This issue continued to expound on the rise of financial innovation and provided an overview of key federal regulations for servicemember financial protection.

My colleagues and I have previously written about the growing role of fintech and the data sharing consumer protection principles. Today's blog post will explore potential fair lending risks with the use of big data and the rise of fintech.

The article discussed how fintech has already produced real benefits to consumers, including increased speed, convenience, and new product offerings that make it easier for consumers to manage their financial lives. Fintech also offers the possibility of bringing banking and financial products to underserved communities and the underbanked.

With that being said, many firms are exploring ways to leverage new data and analytic techniques to extend credit to more consumers. The CFPB has noted that approximately 26 million Americans are credit invisible, which means that they do not have a credit record and another 19.4 million do not have sufficient recent credit data to generate a credit score.

The Federal Reserve's Article is intended to offer some general guideposts for evaluating UDAAP and fair lending risks related to fintech, with a focus on alternative data. Note, fair lending and UDAAP are broad areas of the law where sound legal analysis depends on the specific facts and circumstances.

Background

The Equal Credit Opportunity Act (ECOA) and the Fair Housing Act (FHA) are the two key federal fair lending laws. These fair lending laws broadly prohibit two kinds of discrimination: disparate treatment and disparate impact. In some instances, both theories may apply. Disparate treatment occurs when a lender treats a consumer different because of a protected characteristic (i.e. race, color, religion, national origin, sex, marital status, age).

Disparate impact occurs when a lender's policy or practice has a disproportionately negative impact on a prohibited basis, even though the lender may have no intent to discriminate and the practice appears neutral. A policy or practice that has a disparate impact may violate the law, unless the policy or practice meets a legitimate business necessity that cannot reasonably be achieved by a means that has less impact on protected classes.  

Moreover, Section 5 of the Federal Trade Commission Act prohibits unfair or deceptive acts or practice. The Dodd-Frank Act prohibits unfair, deceptive, or abusive acts or practices. Many states also have town on UDAAP laws. Deception in the financial services industry often involves misrepresenting the terms or costs of financial services products.

Questions to Consider When Thinking about Fintech and Alternative Data

The Consumer Compliance Outlook considers that many firms and financial institutions are exploring new data sources and analytical techniques. The Federal Reserve warns financial institutions to conduct a thorough analysis to ensure compliance with consumer protection laws prior to implementing new data and modeling methods. The article provides a series of questions to help financial institutions determine whether they are appropriately using alternative data. The questions are grouped into two broad categories: basis for considering the data; how the data is being used.

What is the Basis for Considering the Data?

Question #1: Is there a nexus to creditworthiness?

Generally, the more speculative the nexus with creditworthiness, the higher the fair lending risk. In addition to accuracy and reliability, it is important to consider whether the data is representative of all consumers or only a subset.

Question #2: Will the predictive relationship be ephemeral or stable over time?

Financial institutions may want to consider whether the predictive potential of the data is likely to be stable over time or ephemeral. For example, if a model uses online data from social media sites, such as Yelp or Facebook, what happens to the reliability of that data as consumers' online habits evolve?

How are You Using the Data?

Question #3: Are you using the data for the purpose which they have been validated?

The Federal Reserve advises that it is important to ask if the data has been validated and tested for the specific uses. For example, if a financial institution validates a data field for marketing, it does not mean this same data is appropriate to use for underwriting or pricing.

Question #4: Do consumers know how you are using the data?

Consumers generally understand how their financial behavior affects their traditional credit scores. However,  alternative credit scoring methods could raise questions of fairness and transparency.

The ECOA and the FCRA require financial institutions who deny credit to provide consumers with adverse action notices specifying the top factors used to make that decision. The FCRA also requires that consumers receive risk-based pricing notices, if they are provided credit on worse terms than others.

With that being said, it is important that fintech firms, and any banks with which they partner, ensure that the information conveyed in adverse action notices and risk-based pricing notices complies with the legal requirements for these notices.

Certain behavioral data may raise particular concerns about fairness and transparency. UDAAP issues could also arise if a firm misrepresents how consumer data will be used.

Question #5: Are you using data about consumers to determine what content they are shown?

Technology can make it easier to use data to target marketing and advertising to consumers most likely to be interested in specific products, but doing so may amplify redlining and steering risks.

The Federal Reserve stated that the core concern is that, rather than increasing access to credit, these sophisticated marketing efforts could exacerbate existing inequities in access to financial services. Thus, these efforts should be carefully reviewed.

Question #5: Which consumers are evaluated with the data?

Are algorithms using nontraditional data applied to all consumers or only those who lack conventional credit histories? Applying alternative algorithms only to those consumers who would otherwise be denied based on traditional criteria could help ensure that the algorithms expand access to credit.

In closing, the Consumer Compliance Outlook states that fintech can bring great benefits to consumers by enhancing speed, convenience and access to credit. However, fintech is not immune to the consumer protection risks that exist in brick-and-mortar financial institutions. The Federal Reserve encourages financial institutions to ensure that fintech trends and products promote a fair and transparent financial marketplace and that the potential fintech benefits are realized and shared by as many consumers as possible.

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Programming Note. NAFCU's offices will be closed Friday, December 22^nd and Monday, December 25^th in observance of the Christmas holiday. We wish you all a safe and wonderful holiday. We'll be open on Tuesday, December 26th and back to blogging on Wednesday, December 27^th.  Happy Holidays!