Consumer Behavior Determines Risk Management

MBA (8/28/2008 ) Palaparty, Vijay
Changes in consumers’ borrowing behavior and attitude toward credit affects how lenders manage risk, according to panelists in a recent webcast from Zoot Enterprises, Bozeman, Mont.
“Current changes in consumer behavior have been driven by an extreme change in the housing environment, particularly around real estate lending products,” said Tim Bates, a banking consultant. “The stress has caused fundamental changes in patterns of consumer behavior toward credit products.”

Tom Johnson, vice president of new product development at Zoot Enterprises, said data are key to recognizing patterns in consumer behavior. “Reach out beyond traditional data sources and pull together more analytics,” he said. “Lenders should collect every bit of data they can and start running analysis, looking at behavior trends. How are consumers behaving differently as they accept credit and use it?”

Andy Callen, executive vice president of CG2 Direct, Allentown, Pa., said the intersection of marketing and risk management, incorporating technology, can help lenders grow. “Lenders can better use technology to identify small, fractional segments of new or current customers,” he said. “Applying technology to further micro-segment populations, lenders are finding pockets of success."

“Real estate lending has really shut down,” Bates said. “The decline is to preserve capital. Most of the cutbacks have been along traditional lines such as tightening parameters on FICO scores and loan-to-value ratios. FICO scores and LTV ratios are blunt.”

Johnson concurred that tightening has followed a “blunt tool approach. The changes we’ve seen aren’t based on understanding of new consumer behavior but to protect capital,” he said. “What we’ve seen are broad strokes and not selective tightening.”

“We’re also seeing increasing emphasis on manual underwriting as some folks are blaming automated underwriting as an excuse to take your eyes off the ball," Bates said. "However, automated underwriting systems drive effective workflow." He added yhay AUS standardizes data acquisition for analysis.

Johnson said current credit risk scoring models are effective, remaining fairly predictive. “Most institutions are trying to ramp up on turn time on scoring models, however” he said. “They could use scoring models for an extended period of time but there is an urgency to take these models and create new ones, getting into a process of continuous score card adjustment. The analytics necessary to build scoring models are changing rapidly than they have in the past.”

Callen said speed-to-market is good. “The more adaptable these decisioning processes are, the better you can adapt to a dynamic market,” he said. “If you can monitor risk and change, there are advantages if you have speed to jump at it.”

Bates said modeling and technology that could help lenders stay current during market fluctuations.

“Not real-time understanding but near-time understanding of markets is a manageable objective,” Bates said. “There are things you can do in terms of compressing time required—blocking and tackling related to data issues with modeling—that put you in a position where you are not short circuiting time to build a credit scoring model.”

Callen said adaptability is important. “Being able to adjust the analytic process and strategy is a key goal to improve risk management and improve customer development,” he said.