Decisioning data crucial for Chase risk management strategies

SAN DIEGO — Data and analytics go hand in hand with risk management in today’s digitally-driven auto finance market, making it crucial for auto lenders to rely on the right data for their decisioning, Chase Auto Chief Risk Officer Ajit Nalla, said Tuesday during a fireside chat at the Auto Finance Risk Summit.

“It’s important to have the best data,” Nalla said, noting lenders should be aware of consumers’ obligations to other credit issuers with data from credit bureaus.

Internal data, however, is “more powerful than what you get from a bureau,” he said. JP Morgan Chase, for example, leverages consumer deposit data and runs algorithms to understand customer spending patterns, cash flows, income and where a consumer is transacting.

Alternative data, such as rent and utility obligations, too, can paint a valuable picture, especially for consumers with thin to no credit, Nalla said.

Lenders should also take note of what information they need from a consumer at a specific point in decisioning and tailor borrower questions accordingly, he said. “If we randomly ask consumers a lot of questions, they ask ‘why do I have to give it,’ but if you make it more in the context of your vision, you get [what you need].”

When it comes to leveraging data for risk management, strategies should be simple and make the most of the information, Nalla added. “You can’t have very complex strategies with thousands of rules because what happens is you don’t know where your margins are and then you end up having layered risks and concentrations and you can’t govern them,” he said. “That’s where taking all the data and putting them into meaningful scores that can help you to rank order is important.”

Risk strategists should also design testing in a way that “you can learn and feed data back to algorithms and get better,” Nalla said.

“Models are going to have blind spots; they are only as good as the data they saw in the past,” he noted.