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How Neobank cred.ai is Rethinking Conventional Credit Decisioning

By Andra Hrycenko on Dec 22, 2020 2:02:38 PM

Credit underwriting was once more art than science, with individual bank loan officers examining each application. Today, an ever expanding universe of data feeds sophisticated decisioning models.

Yet, even in the increasingly information rich world we live in, underwriting is still an “imprecise” science, according to neobank, cred.ai, co-founder and CEO, Ry Brown.

Recently, Alloy’s Sue Devine spoke with Ry to learn more about his underwriting philosophy as his company prepares to launch a new “premium card for the masses” in 2021.

The More Data, the Merrier (But It’s Never Perfect)

In recent years, interest in new, alternative data sources has grown among credit underwriters. In addition to the traditional FICO credit score, financial institutions can now consult services that provide applicants’ income information, bill payment history, and other indicators of credit worthiness.

This presents both potential peril and promise for underwriters.

The risk, according to Ry, is that the data is still “finite.” At worst, this may mean that the promise of new artificial intelligence solutions may be overblown. He believes that some services may have built sound models but there’s not enough data to really make them useful. At best, it means that each new data point provides potentially helpful information, but none are a singular or definitive source of truth.

On the other hand, by layering alternative sources of data on top of traditional FICO credit scores, underwriters should have a more complete picture of a person’s financial history. Some data points, like a customer’s cell phone bill payment history, may be a good way to filter out the worst risks immediately. Ry pointed out that, “everyone pays their cell phone bills. That’s one of the last things people skip. So, if they have missed cell phone bills, that person is more likely a bad risk and can be flagged for further review.”

Filter Out the Bad Instead of Ranking the Good

Cred.ai is built on the premise that there are hard working, credit worthy people at all income levels (and reckless spenders at all levels too). His philosophy is to focus on screening out the worst risks.

Ry sees traditional lenders as spending a lot of time determining “how good” an applicant is rather than finding and filtering out the truly bad risks. Traditional lenders put energy into answering whether an applicant has an excellent, very good, or fair credit score. People with lower scores are relegated to secured cards and other products that make them “feel less than.”

Instead of worrying about where people fall on this scale, Ry believes a focus on filtering out the truly bad actors is the more efficient and fair way to approach underwriting. He says this is especially true for applicants with thin credit files. Ry believes “no history is good history and that you’re innocent until proven guilty.” Many people with thin credit files may be untrustworthy of credit, not undeserving of it. The onus is on financial institutions to provide products that build or rebuild that trust.

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Hopefully 2021 will see covid-19’s defeat. It may also, however, see a world with continued or increased financial instability for many customers. Financial institutions that can navigate this climate and extend credit safely will have the chance to grow and build trust with customers. 

Ry’s underwriting philosophy emphasizes an agility and pragmatic open-mindedness. A similar outlook may well serve banks of all sizes in a post-pandemic future.

Click here to access a recording of the webinar!

Andra Hrycenko

Written by Andra Hrycenko