High Spenders v. Low Spenders: How to More Effectively Identify Them

Most lenders and financial institutions prefer working with high spenders versus low spenders. However, the best methods for identifying high spenders elude many credit risk specialists. Here are some simple guidelines to help you understand how to better and more effectively identify high-spending consumers in any group.

Knowledge is power

Unlike many financial disciplines, within the credit risk arena a consumer’s past behavior is very often an indication of future behavior. The more you know about the consumers you’re studying, you are better able to identify those likely to spend more and utilize credit more heavily — and more responsibly — in the future.

Time helps tell the story

A snapshot of credit activity at one specific point in time — which is what you get with traditional tools like consumer credit reports — can only tell you so much. You can get deeper insights into a consumer’s credit behavior by analyzing credit data that reflects several dates or periods within the consumer’s overall credit history, also known as time-series or trended data.

This broader analysis allows you to measure the general direction in which a consumer is moving and, in particular, whether the consumer’s spending level is increasing, decreasing or staying the same.

Wider focus helps narrow the selection

This wide lens view allows you to more effectively separate high spenders from lower spenders. Spending behaviors stand out more clearly, regardless of a consumer’s repayment of previous credit balances.

Conventional metrics historically allow a significant percentage of relatively low spenders to be included in what is intended to be the high-spending group. The broader view obtained by following the guidelines above, however, generally results in more effective filtering of consumers in the group according to their credit-usage and spending habits.

Statistically speaking, tests using time-series or trended data have produced an improvement in predictive accuracy ranging from four to seven percent, and have modeled out increases in the average spending level of identified high-spending groups up to 17 percent higher. Of course, these results may vary from one test to another.

Nevertheless, taking the broader view of consumer spending patterns can help credit risk managers identify high-spending consumers much more accurately.

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