Academic journal article Journal of Small Business Management

Small Business Credit Scoring and Credit Availability

Academic journal article Journal of Small Business Management

Small Business Credit Scoring and Credit Availability

Article excerpt

U.S. commercial banks are increasingly using small business credit-scoring models to underwrite small business credits. The paper discusses this lending technology, evaluates the research findings on the effects of this technology on small business credit availability, and links these findings to a number of research and policy issues.


Small businesses are an important part of the economy of virtually every nation. In the United States, for example, small businesses account for about half of all private-sector employment and nonfarm gross domestic product according to the Small Business Administration (SBA). (1) Nonetheless, small firms have historically faced significant difficulties in accessing funding for creditworthy (that is, positive net present value) projects due to lack of credible information about them by potential providers of funds. Small businesses are typically much more informationally opaque than large corporations because they often do not have certified audited financial statements to yield credible financial information on a regular basis. Also, these firms usually do not have publicly traded equity or debt, yielding no market prices or public ratings that might suggest their quality. To address this opacity problem, financial institutions use a number of different lending technologies.

This paper focuses on small business credit scoring (SBCS), a lending technology used by many financial institutions over the last decade to evaluate applicants for "micro credits" under $250,000 ($250K). SBCS involves analyzing consumer data about the owner of the firm and combining it with relatively limited data about the firm itself using statistical methods to predict future credit performance. Credit scores have been widely used for many years in consumer credit markets (for example, mortgages, credit cards, and automobile credits). This has resulted in low-cost, commoditized credits that are often sold into secondary markets, yielding significant growth in consumer credit availability. However, only in the mid-1990s did financial institutions begin to combine the consumer and business information to create scores for small business credits on a widespread basis, and to date, no significant secondary market for small business credits has emerged. Later, we will describe the SBCS technology and its use, review the extant research on its effects on credit availability (broadly defined), and discuss the key research and policy issues related to this technology.

To put SBCS into context, it is one of a number of transactions lending technologies based primarily on "hard" quantitative information used by financial institutions to address the opacity problem. The hard data for transactions technologies are relatively quickly gathered without need for prior contact with the firm and can be relatively easily observed, verified, and transmitted to others. Other transactions technologies using hard information to lend to opaque small businesses include asset-based lending, factoring, fixed-asset lending, and leasing. Each of these technologies is based primarily on a particular source of hard information other than quality financial statements and traded securities, which are not available for opaque small businesses (for example, asset-based lending is based on valuations of accounts receivable and inventory pledged as collateral). (2) For SBCS, the hard information is primarily personal consumer data on the owner obtained from consumer credit bureaus, data on the business collected by the financial institution, and in some cases, information on the firm from commercial credit bureaus. Though SBCS is often used to evaluate opaque small businesses, it may also be used for relatively transparent borrowers to reduce underwriting costs.

As an alternative to the transactions technologies, financial institutions also attack the opacity problem using relationship lending based on "soft" qualitative information gathered through contact over time with the firm, and often with its owners, managers, and other members of the local community. …

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