Sunday, April 14, 2024
HomePortfolio ManagementHow AI Is Helping Lenders Build More Systemic Controls As They Navigate...

How AI Is Helping Lenders Build More Systemic Controls As They Navigate Increasing Regulatory Scrutiny

At the onset of 2023, the Consumer Financial Protection Bureau (CFPB) and the New York State Office of the Attorney General filed a complaint against a large auto lender in the subprime space, alleging that the auto lender misrepresented costs in loan agreements that may have placed customers in high-cost loans on used cars in violation of the Consumer Financial Protection Act of 2010 and New York usury limits.

The scenario represents one of the latest examples of regulators pushing the boundaries by introducing new laws or enforcing existing ones that leverage interpretations that place administrative pressure on lenders and their compliance teams. Many lenders remain susceptible to fines and penalties that are detrimental to their operations and bottom lines.

The importance of systemic controls
Lenders can more stringently mitigate these scenarios through the implementation of systemic controls that help them avoid this additional scrutiny and audit environment. Today, the vast majority of lenders do not have these systemic controls in place to audit the contents of contracts and deal jackets. However, lenders are looking at implementing these controls either through added in-house staff, which is difficult in today’s tight labor market; relying on existing manual controls, which often are susceptible to human oversight or errors; or through external vendor partners who provide artificial intelligence-based software-as-a-service solutions to automate much of the process.

In addition to providing real-time, no-touch loan processing capabilities, today’s AI-powered software enables lenders to comply with regulatory requirements and be audit-ready. The solutions offer policies that are clear and standardized, and lenders are guided through model governance compliance for internal audits while providing expert advice and sample documentation, if necessary.

Common loan defects that affect lenders
Oftentimes, mitigation can take place when today’s new AI compliance software spots any of the following common defects during the loan origination process for F&I add-ons, GAP waivers, or debt cancellation agreements:

1: The add-on product is itemized on the contract, but the product’s contract itself is missing and it is possible that the borrower was never presented with the add-on for review.

2: The add-on product was included in the contract but it was improperly bundled into the front-end amount instead of back-end, so taxes and fees are incorrect.

3: The add-on product was included by the dealer on the contract and a copy of the product’s contract was included in the loan jacket, but the copy was missing the borrower’s signature.

4: The add-on was itemized, included in the contract and signed, but the dealer never presented to the borrower a notice that the product is cancel-able.

5: The add-on product was included in the loan jacket, but it was priced inconsistently, indicating a potential disparate treatment issue, or otherwise sold in a way that is not of material benefit to the borrower.

How AI is identifying loan defects
Model documentation from today’s AI software includes a qualitative assessment of the potential for disparate impact risk in the models built for lenders. The auditing process performs quarterly, quantitative disparate impact assessments. The analyses are based on race, ethnicity, gender, and age (62+), and while the process doesn’t collect race and ethnicity data, it does employ the CFPB’s Bayesian Improved Surname Geocoding (BISG) proxy method for race, ethnicity, and gender using the most recent census data.

The software today leverages advanced AI technology to simplify and automate the process of collecting and analyzing data, with the goal of helping to fund loans as quickly and efficiently as possible while lowering cost to fund, lowering the cost of processing GAP refunds for early payoffs, improving compliance, and lowering the cost of regulatory Matters Requiring Attention (MRAs) and consent decrees related to unfair, deceptive, or abusive acts and practices (UDAAPs).

This requires the right strategic partner to help identify critical defects in deal jackets that would delay funding as they require correction by dealer or a manager exception. By using AI to catch these defects, improper deals can be flagged that are not ready for funding. The right partner leverages this AI software to allow funders to focus on complete deals, enabling their teams to quickly address any identified issues with dealers. It also enables automation of dealer defects, instantly notifying dealers of document defects to reduce contracts-in-transit, and fund deals faster and reduce compliance and regulatory risk.

With the right plan in place leveraging AI, lenders can further reduce friction with dealer partners, and ultimately the end customer. More importantly, lenders can reduce compliance risk and focus on what they do best – asset and portfolio management for a healthier bottom line.

Justin Wickett
Justin Wickett
Justin Wickett is the founder and CEO of Informed.IQ, an AI startup serving the financial services industry that uses machine learning models to classify, analyze, and extract data from documents used in consumer lending, mortgage, and bank account openings. For more information please call 628-299-1650 or email [email protected].