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Harnessing Predictive Analytics for Increased Cash Flow

How statistical modeling technologies are helping companies revamp their credit and collections functions.

By C. J. Wimley | Updated on February 04, 2014
“Big data” is widely discussed these days, among both businesses and consumer groups. As the volume of data that corporations compile increases exponentially, more and more organizations are leveraging predictive analytics technologies to transform that information into intelligence—and, ultimately, value—for the company. A familiar example is the way in which certain online stores suggest items a particular consumer might be interested in purchasing, based on an analysis of his or her prior buying behavior.

Today, many companies are grappling with how to harness their vast data stores, exploring the potential of predictive analytics to support a variety of corporate functions. One department that may soon be revolutionized by predictive analytics solutions is credit and collections. Analytics software can help accounts receivable (A/R) teams increase cash flow by not only prioritizing which customers are contacted by collections staff, and when, but also recommending a method of contact that is most likely to help the organization get its invoices paid fast.

These same tools can help treasurers, who bear the burden of predicting cash flows months in advance. A study conducted by the Aite Group showed that most treasurers are not yet taking advantage of this opportunity. When asked about their methods of cash forecasting, 60 percent of the survey’s respondents said they simply take their current A/R balance, apply an arbitrary percentage, and add that increase or decrease into the previous period’s cash forecast. When the credit-and-collections function can provide treasurers with more accurate projections of the cash flows expected from their collections activities, treasury can produce more realistic cash forecasts.

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