Macroeconomics Key Tool in Analyzing Portfolio Risk

By Ward, Forrest L.; Neubig, Tom S. | American Banker, April 8, 1997 | Go to article overview

Macroeconomics Key Tool in Analyzing Portfolio Risk


Ward, Forrest L., Neubig, Tom S., American Banker


There is no denying the importance of consumer lending. Not only is it one of the fastest growing segments of the banking portfolio, but it also provides some of the highest spreads and yields to the industry.

Although this sounds encouraging, there are some disturbing trends leading many to suggest that consumer lending could be the next credit crisis.

Consumer indebtedness is increasing. In the fourth quarter of 1996, consumer credit outstanding rose by $43 billion, to $1.226 trillion, according to the Federal Reserve.

Bankruptcies, delinquencies, and chargeoffs are all increasing, and the consumer is more highly leveraged today than any time in history. Taken together, these factors could be a recipe for disaster.

How management analyzes and understands the trade-offs between credit risk and the profitability of consumer portfolios will determine the winners and the losers.

It seems every bank's management believes that it is doing a good job and that its competitors are assuming risk unknowingly or with reckless abandon. The key is how management actually analyzes the credit risk and profitability of its portfolios.

We believe lenders should focus on three major areas: portfolio segmentation, scoring systems, and macroeconomics.

Portfolio segmentation and scoring systems are well understood by most institutions even though the effectiveness of their application varies widely. We will focus on using macroeconomics to anticipate trends, modify tactics, and influence strategy to bet ter manage credit risk and profitability.

Consumer portfolio managers have always intuitively considered macroeconomics as part of their managerial decision process. Recently, there has been research concerning the use of macroeconomics to quantitatively predict trends in consumer lending, such a s delinquencies, bankruptcies, and chargeoffs.

This is a developing area that will be a powerful tool in the future and a key differentiator between those managers who are able to seize opportunities in consumer lending and those who flirt with disaster.

The theory is simple. If consumer interest rates rise, the burden on consumers increases and delinquencies should also increase. If consumer indebtedness as a percentage of disposable income increases, credit quality should decrease. If unemployment rises , delinquencies should rise, and so on.

But determining which indicators have the greatest impact on delinquencies, bankruptcies, or chargeoffs is much more complex. Through the use of sophisticated multiple regression analysis, we are able to identify economic factors that will be predictive f or various portfolio segments.

This way, an institution can evaluate which segments of their portfolio have the greatest credit risk under current and future economic conditions.

In addition, we know there is a significant lag between the time an economic indicator changes and the resulting delinquencies, chargeoffs, or bankruptcies occur.

Therefore, using economic indicators with regression analysis can give warning signals to potential problems or opportunities in a portfolio. This technique allows an institution to identify which portfolio segments have the greatest profitability potenti al and the least credit risk and to evaluate various tactical and strategic decisions to enhance overall long term profitability.

For one thing, the risk relationship between different groups predicted by credit scoring models may not be constant over time.

One limitation of credit scoring models is their development of relative risk relationships using past history, holding constant other factors that affect both groups similarly. Are these "other factors" important from a lender's perspective? If they are, what is their impact on consumer credit delinquency?

Delinquency rates rose from 2.3% in the second half of 1981 to 5.4% at yearend 1996. …

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