The new quantify behind qualify: Better data and the consumer credit revolution

A customer walks into a bank to apply for a car loan and finds out they don’t qualify. What happens next? Usually, the bank issues a rejection letter—and indeed, the customer feels rejected.

Then the customer possibly (or probably) applies for credit at a different bank … and the original bank is in turn rejected: They never see that client again.

Can banks change the course and ending of this story? The answer could be as simple as more transparent information for both the bank and the customer.

If lenders can get more accurate and quick portrait of the consumer’s true risk profile, they can make the best offer at the right time. The result? Fewer rejections derived from incomplete or murky credit data.

At the same time, customers who understand the factors that drive credit approval decisions can take actions that improve the chances of qualifying for the credit offers they want.

Banks can also add value for consumers rejected for a specific credit offer. This begins when they provide tools that raise awareness of the steps customers can take over time to qualify for that same credit offer or other credit products. 

Tapping into a more transparent credit environment also generates robust data that pinpoints qualified borrowers earlier in the decision process, unlocks opportunities to improve underwriting and provides a path for borrowers to better qualify.

A different kind of credit denial: Current marketplace problems

Improving the consumer credit market’s efficiency requires addressing these existing limitations:

1. Lenders who use insufficient data: Lenders now have increased access to consumers’ financial information, including credit scores. While this information reflects the current ability to qualify for offers, it does not predict intent, goals or upcoming changes that may impact credit worthiness.
2. Consumers who don’t maximize credit worthiness potential: The complex nature of credit scoring means consumers may fail to connect three crucial points: the financial decision, the corresponding credit score impact and related ability to qualify for credit offers. Prevalent channels for credit offers further cloud the picture; they often disregard consumers’ ability to qualify for and lack the information that allows them to assess their chances.  
3. Credit files that contain inaccurate data. The current consumer credit infrastructure is fraught with errors, inaccurate data and stale information in consumers’ files. All this leads to credit scores that don’t reflect current credit worthiness. In 2016, consumers filed more than 186,000 complaints related to credit reports with the Consumer Financial Protection Bureau. These complaints represent hundreds of thousands of customers with lower credit scores due to reporting errors. Inaccurately low scores limit the potential customer pool, while on the other hand missing data may not reveal a borrower whose credit score doesn’t reflect how risky they are.

Past due: Filling the data gap

Lenders can increase the effectiveness of data to evaluate credit approval when they expand the sources to assess a borrower—and thus enable more accurate underwriting with a more comprehensive view of the customer’s true financial capabilities.

The additional data allows banks to assess borrowers with thin or non-existent credit files and present opportunities to qualify for certain offers.

Lenders can also increase conversion when they obtain trended data on each consumer’s credit worthiness and then offer specific products only to those who will qualify for them in the near future. Trended data shows the history of how a credit score has risen or dropped based on changes in the borrower’s financial situation. This, along with mathematical modeling, can estimate a consumer’s credit score in the near term.

With the right information, banks can identify the consumer’s needs for specific credit products before that consumer actively applies, and that can create increased marketing opportunities with improved outcomes for all.

Lenders can provide tools to their customers and prospects that allow consumers to better control of their financial outcomes. One of the best ways to capture a denied credit customer—and lift them beyond their “rejected” state, financially and emotionally—is to show them the best actions to take so that they can qualify for the products they want, or alternative credit options.

Newly developed applications driven by artificial intelligence provide unprecedented access to modeling actions that impact credit scores. These actions can be executed within the lender’s mobile or online app, capturing that data for use in future credit decisions. This same access can ensure that credit report is complete and accurate—which in turn boosts the chances to obtain the credit product that fits a consumer best.   

We are amidst a data revolution, with developments in the FinTech broadening opportunities for lenders to provide credit products to consumers. Meanwhile, these same innovations allow consumers optimal access to these offerings. This increases customer satisfaction and a lender’s growth.

But it also means something more. The bank that leverages data in the customer’s favor makes the leap from earning business to earning loyalty. To that end bear in mind consumers, rejected or otherwise, will keep close score.   

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Chad Swensen is CEO at Lantern Credit, LLC, a FinTech that integrates and enhances key components of the consumer credit, debt, credit reporting and scoring industries.