Financial Industry Crisis Spurs Reevaluation Of Risk Management

It isn't just about one institution's risk, but rather about how risk is shared across the industry and entire economy.

InformationWeek Staff, Contributor

November 13, 2009

3 Min Read

Data-Driven Decisions

More than 93% of banks require at least nine months to come up with new risk policies, and 64% need at least 12 to 18 months to change course, according to TowerGroup analyst Bobbie Britting. That's not fast enough in an economy where even someone with a high credit score and flawless payment history can enter bankruptcy at the drop of a pink slip.

Zoot Enterprises, a Bozeman, Mont., vendor of credit decision and loan origination technology tools, maintains that banks should be able to change course in about a week. Its tools let risk managers experiment with new data and new risk models.

Zoot is helping one of the top 10 U.S.-based banks implement a fast-moving process to let risk analysts include new information in their credit models. For instance, data about payments on cell phone accounts are "fantastically predictive," says Zoot marketing director Eric Lindeen. "If someone's five days late several months in a row, it's an indication that other accounts will also be bad soon."

Similarly, data about recent payments to utility companies, usage of payday loans, and various data from the public record also can provide clues as to a customer's changing financial status. Nevertheless, these sources haven't yet been incorporated into the most commonly used credit bureau scoring models. "They'll eventually incorporate it," Lindeen says, "but today there's useful data out there that you can't get from the bureaus."

This proliferation of risk-related data puts banks in the new position of having to negotiate access with multiple information providers. Then, once they have access to the data, risk analysts must develop their own hypotheses on what data contains predictive ability related to their own customers, test those hypotheses, and deploy their new risk models into the lending process.

Financial institutions that fail to incorporate this data into their risk models will have fewer options in the new economic climate. If stuck with a loan decision process from mid-2008, a lender may still not be able to discern between good risks and bad risks. Meantime, its best option may be to raise rates across the board just to be safe. This is especially true following passage of the Credit CARD Act of 2009, which prevents banks from raising interest rates on new accounts for 12 months. If you're really not sure if someone's a good risk, and you know you must maintain the person's interest rate for an entire year, the safest choice is to set the rate high.

However, a bank that knows how to differentiate risks will be able to offer lower interest rates to good risks, while letting competitors unwittingly take on the bad risks. That's the strategy of the top 10 bank working with Zoot. "They see the ability to build better, faster risk models as a competitive differentiator," Lindeen says.


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