Skip to Content
chevron-left chevron-right chevron-up chevron-right chevron-left arrow-back star phone quote checkbox-checked search wrench info shield play connection mobile coin-dollar spoon-knife ticket pushpin location gift fire feed bubbles home heart calendar price-tag credit-card clock envelop facebook instagram twitter youtube pinterest yelp google reddit linkedin envelope bbb pinterest homeadvisor angies

Collection Agency Illustration

I am all familiar with the traditional methods of providing credit scores. But banks increasingly are relying on dozens of scores that reflect a variety of data sources, analytics, and use of artificial intelligence technology.

The use of AI offers lenders the ability to get a precise look into someone’s creditworthiness and score those previously deemed unscorable.

But such scoring techniques also bring uncertainty: What it will take to convince regulators that AI-based credit scores are not a black box? How do you get a system trained to look at the interactions of many variables, to produce one clear reason for declining credit? Data scientists at credit bureaus and banks are working to find answers to questions like these.

The benefits of AI-powered credit scores

There are two main reasons to use artificial intelligence to derive a credit score. One is to assess creditworthiness more precisely. The other is to be able to consider people who might not have been able to get a credit score in the past, or who may have been too hastily rejected by a traditional logistic regression-based score. In other words, a method that looks at certain data points from consumers’ credit history to calculate the odds that they will repay.

Machine learning can take a more nuanced look at consumer behavior.”

Consumers with several chargeoffs in their histories would most likely be considered high-risk borrowers by most traditional models. But an AI engine might perceive mitigating variables; though the consumers might have skipped payments on three debts in the past 24 months, they have paid on time consistently for the past year and have successfully obtained new lines of credit.

It looks like bad performance or bad history is in your past. That would be a simple example of how an AI world might help cast data in a more positive and more accurate light.

AI-based credit scoring models let Elevate make sharper predictions of credit risk, approve the right people, and offer better pricing to people who deserve it.

Elevate is deploying its new, AI-based models gradually, starting with 1% of potential borrowers, testing the results, and gradually applying them to more people.

Carolyn Secor P.A. focuses its practice in the areas of Bankruptcy and Foreclosure Defense in Clearwater, Florida. For more information, go to our web site or call 727-335-7151.