JPMorgan to Tap New Markets with Cash Flow Underwriting

JPMorgan Chase plans to expand its underwriting toolkit to gain a more accurate picture of a borrower’s finances and serve more customers. The company aims to use cash flow underwriting and data from credit bureaus in other countries to inform lending decisions, according to American Banker.

These enhanced models provide credit card issuers fresh ways to evaluate creditworthiness — and any new strategies JPMorgan adopts could serve as useful case studies for others looking to refine their own practices.

With more than $200 billion in credit card loans, JPMorgan Chase isn’t forging into new underwriting territory on its own. The company has chosen to partner with Nova Credit, a financial technology firm specializing in analytics and credit infrastructure, to power its lending evaluations.

The collaboration suggests that partner programs may help smaller issuers reach their goals faster and more effectively than building in-house solutions. that partner programs may help smaller issuers

JPMorgan Chase is partnering with Nova Credit to expand its underwriting capabilities.

The bank plans to use Nova Credit’s Cash Atlas product, which automates cash flow underwriting. The tool uses data on a person’s assets, expenses, and income to form a picture of their financial health.

Nova Credit’s Credit Passport offering will enable JPMorgan Chase to access credit bureau data from 20 countries outside the U.S. A press release on the partnership indicates that Nova Credit’s solutions will position the bank to serve more people in the U.S. who don’t have a robust credit history.

“Chase is committed to being the bank for all and tools like Cash Atlas and Credit Passport will help with this mission by giving us a more comprehensive view into each individual and their credit needs,” Chris Reagan, President of Chase Branded Cards at JPMorgan Chase, said in the release.

Traditional credit models tend to lean heavily on factors like an individual’s credit history and credit utilization ratio. Lenders often turn to scores from companies such as FICO and VantageScore to assess how reliably a borrower repays debt.

But traditional credit models may exclude some potential borrowers, including people who’ve recently moved to the U.S. and don’t have a credit history in the country. Younger people who haven’t had much experience with credit may also face a disadvantage when lenders assess their financial background via traditional methods.

Cash flow underwriting gives lenders a framework they can use to extend credit to people they may have otherwise turned away.

We checked in with Jason Rosen, Founder and CEO of Prism Data, to learn more about cash flow underwriting and how it’s changing the borrowing game for lenders and their customers. Prism Data uses transactional data from bank accounts to create credit scores and attributes.

Cash flow underwriting, and the use of CashScore in non-prime lending, has grown rapidly over the last year, said Rosen. CashScore is a solution Prism Data offers that takes deposit account data and transforms it into risk predictions.

Lenders who use cash flow underwriting may be able to grow their market share by reaching people who are credit invisible.

“There are tens of millions of people in the U.S. that don’t have credit scores or don’t have representative credit scores,” Rosen told us. “There’s a lot of folks whose credit scores are maybe lower than their actual risk profile.”

Rosen said that he and his team have found that analyzing someone’s income and their spending and savings habits can tell a lender a lot about their financial health and risk profile.

Cash flow underwriting constitutes a fundamental shift in credit decisioning, giving companies a dynamic lens they can use to examine a person’s creditworthiness, wrote Stewart Watterson, a Strategic Advisor for Datos Insights’s retail banking and payments area, earlier this year.

“Traditional credit evaluation methods, while historically reliable, struggle to capture the complete financial picture of modern consumers, particularly given the rise of nontraditional income sources and alternative credit products,” Watterson wrote.

Conventional credit models look at a person’s track record of repaying borrowed funds to predict whether they’ll be able to pay back a loan in the future. But Collin Galster, Nova Credit’s Chief Operating Officer, indicated to American Banker that this approach may not give a lender the whole story on a potential borrower.

“It’s true that someone’s demonstrated ability to have repaid loans in the past is an important data point in predicting their future likelihood to repay,” Galster said. “But it can miss certain information disproportionately for certain populations, and the ways in which it misses are artifacts of the way our system’s set up.”

JPMorgan Chase stands to miss less of that information, and add more responsible borrowers to its customer base, by using cash flow underwriting and credit bureau data from foreign countries in its decisioning practices.

Many consumer lenders have lost confidence in relying solely on traditional credit scores and files to make lending decisions.

Datos Insights surveyed 434 consumer lending companies last year to learn about their lending decisions. The company found that 58% of those institutions are somewhat less confident than they were one year earlier in making consumer lending choices based solely on traditional credit files and scores.

Consumer lenders face growing competition, especially from new entrants offering buy now, pay later services that chip away at credit card market share. But those adopting JPMorgan Chase’s approach — using new methods to evaluate borrowers — could gain an edge over rivals.

Lenders may have strong products to attract new customers, but even the best products can fall flat if lenders’ underwriting standards are so rigid that too many applicants are turned away.

“We believe this is the future of consumer underwriting, helping to responsibly serve more people through the power of cash flow analytics,” Galster said.