The Predictive Power of Economic Indicators in Consumer Credit Risk Management
Liu, Jiong, Xu, Xiaoqing Eleanor, The RMA Journal
A study by Chase Manhattan Bank and Seton Hall University uses U.S. macroeconomic data and industry-wide credit card charge-off data to examine the predictive power of economic indicators in consumer credit risk management. The study finds that changes in economic variables, such as household debt service burden, unemployment rate, consumer confidence index, inflation rate, personal bankruptcy filings, and stock market returns, have strong forecasting power for changes in the consumer credit card charge-off rates. These indicators can be incorporated into credit risk modeling to enhance risk management in the credit card industry.
$1.72 trillion in U.S. consumer credit outstanding can give pause to the retail lender. This was the amount (excluding real estate mortgages) as of September 2002 and included $720 billion in revolving debt and $1 trillion in nonrevolving debt. Revolving debt--credit repeatedly available up to a specified amount as periodic repayments are made--carries its own red flags, having grown from 15% of the total consumer credit outstanding in 1980 to 42% in 2003. In the U.S., most revolving debt is in the form of unsecured credit card loans. With the rising level of credit card debt, charge-offs on credit card loans also increased dramatically--from 2.0% in 1985 to 6.4% in 2002. Tremendous growth in credit card debt, coupled with a substantial decline in consumer credit quality, signals the need for intense risk management focus on the evaluation of a new applicant for credit, increases or decreases in credit lines, transaction authorizations, balance consolidations, collections of credit card debt, and other related account servicing and management practices.
Managing Credit Card Risk
As for any business, credit risk management in the consumer credit card industry aims to measure and control the risk exposure to achieve maximum profits while limiting exposure to defaults, that is, charge-offs. Credit card issuers typically integrate business strategic analysis with legal and regulatory constraints to establish credit policy and guidelines. Credit policy helps an institution to develop strategies consistent with the profitability expectations of the institution within an expected level of asset quality.
At the heart of consumer credit risk management is measuring and controlling the probability of default (PD); yet consumer risk has yet to receive the level of attention as its commercial counterpart.
The corporate bond market has provided an important function of market discipline on corporate risk-taking behavior.
* Ratings agencies (such as S&P, Moody's, and Fitch) constantly evaluate the credit risk of companies and downgrade the credit ratings of their debt instruments when increased level of credit risk is observed.
* Debt market investors react to a downgrade with a higher required yield and lower pricing on the traded debt instruments.
The relationship between the default risk in the corporate debt market and general economic environment has been widely researched, resulting in the general consensus that macroeconomic conditions directly affect the credit-rating transitions and PD. In the consumer credit area, the role of the ratings agency and the debt market disciplinary function is replaced by the consumer credit bureau reporting agency. Financial institution and other retail lenders supply account and payment information about their customers on a regular basis. The agency obtains additional information from federal, state, and county courts, then combines the credit record and public record to create a credit profile for each consumer. Card issuers rely on credit bureau scores, along with customized in-house data, because the information is based on updated, objective, comprehensive information, such as transactions data, debt to income burden, and payment history. The applications of credit bureau scores range from credit risk evaluations to account performance prediction. …