On January 6, 2016, the Federal Trade Commission (the “FTC”) released a report titled “Big Data: A Tool for Inclusion or Exclusion? Understanding the Issues” (the “Report”). The Report was the result of a public workshop held on September 15, 2014 and hosted a number of participants from big data constituencies. The workshop highlighted the potential positive aspects of “big data” including opportunities for consumers and examined the need to potentially protect consumers from those opportunities. The workshop consisted of four panels addressing the following topics: (1) current uses of big data; (2) potential uses of big data; (3) the application of equal opportunity and consumer protection laws to big data; and (4) best practices to enhance consumer protection in the use of big data.
Why is Big Data Important
The Report examines the way that companies utilize big data as a way to: increase revenues, promote customer loyalty through better customer service; incent or reward customers by offering them different prices or discounts, tailor advertising for financial products based on income or other considerations, and assess credit risks of individuals using nontraditional credit scoring methods and assess populations using “aggregate scoring models.”
Phases of Big Data
The Report outlines the four phases in which big data operates: collection, aggregation, analysis, and use. Collection of data can occur through a variety of sources, such as mobile devices and computers, and in a variety of ways such as cookies, browser and device fingerprinting, and history sniffing. Certain entities combine data from disparate sources (often referred to as data brokers), ultimately storing billions of data points on nearly every U.S. consumer, in order to build profiles about individual consumers that will be helpful to corporations wishing to target those consumers. Analysis of data can be descriptive (based on actual past actions of a consumer) or predictive (generating new data points). Data may be gathered for one purpose, but ultimately used for another, and the Report focuses on how companies use big data both for the benefit of consumers or to build ways to selectively exclude consumers.
Positive Uses of Big Data
In describing the positive ways in which big data may be used by institutions, the Report outlines the following concepts: (a) increase educational options for students by providing them access to more advanced institutions and classes, (b) provide more reliable and consistent healthcare both (i) at an individualized level and (ii) to underserved communities, and (c) increase employment opportunities for minority populations. However, key for financial institutions is the ability of big data to provide alternative credit modeling and scoring methods as well as additional indications of creditworthiness outside of the more traditional methods. This may allow financial institutions to provide credit to individuals that have previously been excluded from the traditional credit market because they were deemed “unscorable”.
Negative Uses of Big Data
While exploring positive benefits of big data, workshop participants also discussed big data’s potential to inappropriately exclude applicants and potentially to perpetuate existing discriminatory practices in education, employment, and credit decisions. The ways in which this exclusion can occur includes poor, incomplete, unrepresentative or inaccurate data. Another concern is that there may exist uncorrected biases in underlying consumer data. For example, one academic has argued that hidden biases in the collection, analysis, and interpretation stages [of what?] present considerable risks. If the process that generated the underlying data reflects biases in favor of or against certain types of individuals, then some statistical relationships revealed by that data could perpetuate those biases. When not recognized and addressed, poor data quality can lead to inaccurate predictions, which in turn can lead to companies erroneously denying consumers offers or benefits. Although the use of inaccurate or biased data and analysis to justify decisions that have harmed certain populations is not new, some commenters worry that big data analytics may lead to wider propagation of the problem and make it more difficult for the company using such data to identify the source of discriminatory effects and address it.
Maximizing Benefits and Minimizing Risks
The workshop and the Report concluded with a discussion of appropriate law and policy considerations for companies that use big data. The discussion included whether companies are adequately taking steps to comply with various consumer protection statutes such as the Fair Credit Reporting Act (the “FCRA”), and the Equal Credit Opportunity Act (the “ECOA”) among others.
Workshop participants examined current compliance issues involving financial institutions and (1) rules for complying with the FCRA and (2) advertising considerations under ECOA. FCRA generally applies to credit reporting agencies (“CRAs”) and persons furnishing information to CRAs and requires them to: (a) implement procedures to ensure the accuracy of consumer reports, (b) provide consumers with access to their own information, along with the ability to correct any errors, and (c) only provide consumer reports under certain specified permissible purposes. Traditionally CRAs have included credit bureaus and others that provide particularized services for making consumer eligibility decisions, but recent enforcement actions by the Federal Trade Commission demonstrate that data brokers that compile non-traditional information may also be considered CRAs and thereby may be subject to the FCRA. With regard to advertising considerations under the ECOA, (x) creditors must be careful not to make oral or written statements, in advertising or otherwise, that refer to a prohibited basis for credit decisions (such as race, gender, marital status, etc.) that may tend to discourage a reasonable person from making or pursuing an application; (y) creditors must maintain records of prescreened solicitations and the criteria used to select potential recipients, and (z) even if credit offers are open to all who apply, creditors should monitor for potential discrepancies in subsequent lending patterns and the terms and conditions of the credit received by borrowers.
In addition to the above, companies using big data should also monitor for (1) general policy considerations such inappropriate selectivity of data sets; (2) data model accounts and whether outside biases exist relating to race or other improper factors; (3) back-testing the accuracy of data and predictions based on the data; and (4) whether the use of big data creates ethical or fairness issues as a result of companies making decisions using information that would not normally be available to the company and in fact might be impermissible in the current situation.
Summary and Further Information
Big data has big, positive potential to help individuals, companies, and populations. However, companies using big data must take precautions that they do so in a way that seeks to prevent improperly excluding people from credit, educational, and employment opportunities.