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Credit Behaviors of “Unscorables” (Hint: They Aren’t All Alike)

What are the credit behaviors of the millions of US consumers who don’t currently have FICO® Scores?

We’ve just published new research on how to safely and responsibly extend credit to these “unscorable” consumers. As part of that study, we took an analytical deep dive to better understand their credit behavior. Since our goal was to help expand credit access, we focused on those within this group who actually apply for credit. These are the consumers for whom extending scoring can make the greatest difference, and we wanted to be able to more accurately assess their credit risk.

We found that these consumers differ from the mainstream credit population—and from each other. As a whole, unscorable applicants are more risky. Their overall default rate is almost three times higher than for scorable consumers.

Yet risk levels vary considerably within this population. The graphic below shows unscorable applicants separated into risk bands, using a simple segmentation system based on the quantity and quality of information in bureau files. Bad rates (based on those within each segment who go on to obtain credit) range from 6.2% to 34.2%. Bads are defined as 90+ days past due.

That’s still very coarse separation. To differentiate the risk in greater detail, we need additional data.

Besides risk level, we discovered that other credit behaviors also vary. For instance, the type of credit sought varies significantly by segment. Consumers in the Lost Access to Credit segment are most likely to seek out telecommunications-related credit. Those in Credit Retired and No Credit File segments tend toward credit cards or bank products.

Ultimately, it’s not possible to score these consumers accurately without taking into account these subtle but important distinctions in credit behavior. How? Stay tuned to our blog, where I’ll share more of our research to answer that question. Or for instant gratification, you can get all our research findings now in a new Insights white paper: Can Alternative Data Expand Credit Access?

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