TransUnion has integrated employment with income data to better reflect consumers’ ability to pay as economic dislocation and unemployment rates continue to strain the global economy.

TransUnion partnered with a leading payroll provider that will provide access to tens of millions of active employment records through a direct API integration, Chief Global Solutions Officer Tim Martin told Bank Innovation. He declined to name the partner, and noted that the data is updated every pay cycle to supply the most recent view of a consumer’s employment status and income. Because TransUnion’s architecture to facilitate third-party data is core to its infrastructure, no architectural changes were necessary to support the connection, Martin said.

Employment and income data have become critical components to lenders’ decisioning since the coronavirus pandemic effectively shut down several facets of the U.S. economy. The U.S. unemployment rate declined by 50 basis points in September to 7.9%, according to October data released by the U.S. Department of Labor. And while the unemployment rate has declined for five straight months, the September numbers still constitute a 4.4% increase from February levels.

By a different measure, that’s 12.6 million unemployed Americans in September compared with 6.8 million in February.

“This dataset is an asset that TransUnion has been interested in, and talked to potential partners for near a decade, but only recently did both TU and our partner make this a top priority to get the deal done,” Martin said. “The current process has been cumbersome for too long; consumers often have to provide their own data or lenders subscribe to separate processes,” he said. The new income and employment verification solution will be offered as an add-on to TransUnion’s existing credit and model reports.

COVID-spurred factors have made it difficult for lenders to accurately underwrite consumers and forecast risk in their portfolios, according to industry experts during a virtual panel session at LendIt Fintech USA in September. Predictive models that rank-order risk could see as much as 35% degradation, and the sheer randomness at which COVID-19 impacts people will make it challenging for lenders to be proactive in tweaking or rebuilding those models, at least until payment reporting normalizes and consumers roll off forbearance.

“Evolving customer spending, evolving payment behavior, government response, business operations changing based on shutdowns will continue to affect data and hence the predictive power of models,” said Swati Bhatia, formerly Stripe’s chief payments risk officer, at the Lendit Fintech panel. “That’s the crux of it: Everything will keep changing in how we look at data and prediction in matters of days and weeks, not even months.”

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