Alternative data, AI will shape lenders' decisions

Editor's note: The original version of this story misstated the name of FICO Score XD. This story is now corrected.

LAS VEGAS -- Auto lenders are employing so-called alternative data and, potentially, artificial intelligence for many purposes, according to panelists at the American Financial Services Association's annual Vehicle Finance Conference here last week.

A key use is approving and disapproving loan applications, which is likely to create friction with dealers, especially as artificial intelligence catches on. When bigger, wider sets of data affect the decision on top of traditional measures, most notably credit history, it can become impossible for a lender to explain precisely why an individual loan got turned down.

F&I managers may see, for example, customers whose credit scores look acceptable be rejected for loans as a result of considerations derived from alternative data.

"Would you be comfortable if you don't know how you got there? Are you comfortable with using that?" said Scott Cooke, chief risk officer at Toyota Financial Services. "These AI systems are not going to give you the direct path, the coding, to get to that."

There were separate sessions at the AFSA conference for alternative data, which is already in widespread use, and for artificial intelligence, which draws on, and some have referred to as, Big Data. AI is still on the drawing board for auto lenders. In both sessions, panelists set out to define the terms.

Alternative data is loosely defined as data that's not traditionally tracked by credit bureaus, panelists said. They noted, though, that some credit bureaus have begun gathering alternative data, too. Common examples include credit history for cable TV, mobile phone and utility bills and salary information.

Shafi Rahman, principal scientist for Fair, Isaac Corp., which produces the widely known FICO credit scores, said in the AI session that FICO has developed a credit score that takes into account alternative data, called FICO Score XD.

Alternative data and AI are not all bad news for dealers. Doug Clyma, senior vice president for risk management at GM Financial, said alternative data can "turn a thin file to a slightly thicker file," giving lenders enough to go on to approve a loan that would be impossible otherwise.

He said GM Financial has been using alternative data for eight years, starting in the subprime segment and later adding its use in prime segments.

FICO's Rahman said the FICO Score XD method means that "15 million more adults in the U.S. have access to credit."

In a straw poll of lenders announced at the AFSA conference, 50 percent said they already use alternative data; 18 percent said they are currently implementing or testing it; 18 percent said they are considering using it in 2018; and 9 percent said they are considering using it in 2019 or beyond. Only 5 percent said they were not considering using alternative data at all.

"Anywhere you use a risk score today … you can use alternative data as another source of information to make decisions," Clyma said. "It tells you stability, willingness, ability to pay. That's really where the power is, leveraging information that is correlated with credit risk."

Sang Kim, vice president of risk at subprime specialist Consumer Portfolio Services Inc., said that like other lenders, her firm uses both alternative and traditional credit bureau data. "What weight do we give alternative data vs. traditional? That's my secret sauce. It really depends what segment you are referring to. In prime, you might give less weight to alternative data," she said.

Kim said alternative data is a subset of Big Data, or AI, which encompasses pretty much everything. "Big Data is everywhere. Alternate data is part of it," she said.

FICO's Rahman said, "The way I think about AI is it's a system that has seemingly superhuman cognitive abilities." He said the concept has been around for decades, but it has become a hotter topic in the past 10 years as a result of what he called major breakthroughs in how to "glean deeper and deeper insights into sparser and sparser data."

Consultant Alecia Bridgwater said the use of Big Data could include, for instance, data from a vehicle's onboard diagnostics ports, so lenders could monitor crash reports, driving behaviors and the mechanical health of a vehicle.

Toyota Financial's Cooke, a panelist at the AI session, acknowledged auto lenders have their work cut out for them reconciling dealers and their staffs to credit decisions based on new criteria. "We will figure it out together," Cooke said on the sidelines following the panel discussion. "But there's going to be a lot of change management."