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Doing Business with Small Business.

By Bronstein, Scott
Publication: Business Credit
Date: Monday, November 1 1999

The predictive power of blended models in assessing small business credit risk

The entrepreneurial spirit is alive and well, and living in America. In the last decade, thousands of well-educated and seasoned professionals, many of them downsized

mid-career during the recession-ridden 80s and 90s, have joined the ranks of the self-employed. "Relieved" of their former positions and pension plans, many have seized new opportunities afforded by the Internet, e-commerce and a growing corporate trend toward outsourcing tasks once done in-house.

By 1994, small business had become the growth engine of economic recovery, and it now constitutes a considerable force in the marketplace. Moreover, as corporate mergers and reorganization continue to displace workers, small business start-ups are only likely to increase. Financial institutions and other organizations can ill-afford to ignore the presence of this burgeoning market segment. But neither can they afford to overlook the relatively high-risk, low-margin nature of small business generally. Making loans and extending credit within this segment can be dicey, and companies eager to capitalize on its robust growth have come to recognize that it can only be leveraged profitably and without excessive exposure through risk management techniques tailored to its particular volatility.

With increasing frequency marketing and risk management methods honed in the consumer credit arena are being used to evaluate commercial enterprises. Credit risk scoring has proved especially useful in answering the demand for higher productivity at ever-lower costs. By applying statistical analysis and automated decision processing to credit and marketing functions, financial institutions and businesses following their lead have drastically reduced credit decision turnaround times. Many have begun applying risk scoring to the direct marketing selection process as well, thus enabling organizations-often for the first time-to establish consistency between targeting (direct marketing) and acquisition (application processing) strategies. However, in applying risk scoring techniques to small businesses, problems arise stemming from the often limited amount of commercial credit data available.

While the personal credit history of small business owners is frequently more plentiful and/or readily available than credit data for the business itself, some risk managers refrain from using it for commercial decisions due to the cost and implications of complying with the federal Fair Credit Reporting Act (FCRA). Others, while conceding the value of consumer data, disagree over the point at which predictive power shifts from consumer to business data in the life cycle of a small business.

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