Separating the signal from the noise, AI-powered analytics deliver credit risk management that’s predictive, insightful, and regulation-friendly
It’s a fact of life in the financial services industry: FCRA regulations mandate that loan decisioning be explainable. If a loan applicant is turned down, he or she has the legal right to know why. To ensure compliance, any yes/no lending decision needs to be explainable.
So where do AI-powered analytics fit in? Today’s advanced technologies use both linear and non-linear analysis to deliver deeper and more accurate results. But can this non-traditional data explain a simple yes or no decision? The short answer: yes. Our data scientists use sophisticated AI techniques that combine linear and non-linear analysis, deriving benefits from each approach. Enlisting this multi-faceted approach, it’s possible to separate the signal from the noise to produce insights that are both predictive and explainable, even if the data behind the decision doesn’t lend itself easily to linear analysis.
It’s called Explainable AI, and when combined with our Credit Reporting (CRA) partners it gives lenders the confidence they need to explain their credit decisions while using uncorrelated alternative data.
Federal agencies agree on alternative data in Loan Decisioning
In a recent interagency announcement, The Board of Governors of the Federal Reserve System, Consumer Financial Protection Bureau, Federal Deposit Insurance Corporation, National Credit Union Administration, and Office of the Comptroller of the Currency recognized “alternative data’s potential to expand access to credit and produce benefits for consumers,” and cited the importance of “a well-designed compliance management program” to analyze relevant consumer protection laws and regulations.
You can read the full statement here.
Accelitas is already enlisting alternative data to expand fairness and opportunity in lending, creating financial access for millions. Through AI Lift, our AI-powered Credit Risk Web Service, we help identify and approve the millions of creditworthy customers that traditional credit screening miss — from GenZ and recent immigrants, to a growing population of Millennials who no longer follow the established benchmarks for saving, spending, and banking. AI Lift’s predictive analytics help give more people the credit they deserve, while opening up huge new opportunities for lenders to grow their business. Societal behaviors are changing so it only makes sense to use new strategies to lift credit and create financial access for more potential borrwers.
And thanks to Explainable AI, those decisions can be fair and compliant. It’s a win/win/win scenario.
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