Banking
Customer input is key to ending banks’ discrimination
Global Banking and Finance Review
Company
When faced with problematic issues, banks often begin addressing concerns at the policy- and product-level. Now, it’s time to begin at the customer-level.
When faced with problematic issues, banks often begin addressing concerns at the policy- and product-level. Now, it’s time to begin at the customer-level.
With the Consumer Financial Protection Bureau officially stating that discrimination in any financial product is illegal, banks will need to prioritize pinpointing customer frictions when using their products. Understanding their customers’ concerns starts with exploring customer narratives and identifying the problems they share in their complaints.
Customers tell their banks about the frictions they experience, and customer complaints provide a window into consumers’ perspectives. As stated in the CFPB’s Consumer Laws and Regulations about UDAAP, “Even a single substantive complaint may raise serious concerns that would warrant further review. Complaints that allege, for example, misleading or false statements, or missing disclosure information, may indicate possible unfair, deceptive, or abusive acts or practices needing review.”
Yet, today, banks do not fully leverage customer conversations. As a data source, customer narratives are messy and require new technologies and analytic capabilities. All too often, severe complaints are not escalated, and they are disregarded as outliers, rather than leading indicators.
As banks prepare for their investigations and supervisory exams, including fair lending, fair treatment, and equity, their customers’ narratives can lead them to the specific practices, operational issues, or communication vehicles which explicitly or implicitly suggest discrimination.
In fact, using technology that’s fueled by a decade of CFPB customer narratives, we have found that anywhere between 2-5% of complaints suggest perceived discrimination. Isolating these customer complaints begins the process of addressing the policies and practices that require review.
Using natural language processing and machine learning techniques – which can be leveraged in positive ways, customer narratives that suggest discrimination can be identified based on the protected classes defined by the Fair Credit Reporting Act.
One example worth considering is customer complaints about payment terms. If banks review their policies without customer input, they may not see how the payment terms negatively impact certain groups of customers. That’s why dissecting customers’ words about payment terms is critical.
Banks tend to prepare for their safety and soundness investigations at the product and policy level. Given the multitude of methods used to enforce interdependent policies, this approach can be time consuming and labor intensive – and won’t work for weeding out discrimination.
Customer input is key for efficiently and effectively identifying discrimination – and preventing it from rearing its ugly head. For banks to avoid the CFPB’s expansive new punishment for discrimination, one thing is certain: they need to start listening to their customers.
Marcia Tal is the CEO of Tal Solutions® and the Founder of PositivityTech®: The Science of Transforming Negatives to Positives®. She is also a former Citigroup Executive Vice President of Decision Management.
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