Financial Update (April-June 1999)
Credit Scoring in Small Business
Small businesses have traditionally relied on established relationships with local banks as an avenue for obtaining credit, but credit scoring may end the need for such relationships.
In low- and moderate-income (LMI) areas, small business lending faces additional hurdles. Banks may have concerns about making small business loans in LMI areas because they may have fewer branches that can establish business relationships in these areas. Banks may also be wary of LMI areas in general as places where businesses may have difficulty thriving or even surviving. On the other hand, the pressure exerted by the Community Reinvestment Act for banks to lend in LMI areas may offset the loan-deterring characteristics of these areas' businesses.
Credit Scoring Small Business Loans
One possible solution to some of the information asymmetry problems banks face in small business lending, particularly in LMI areas, may be the use of credit scoring. In the past few years, some banks have begun using this method to assess small business loans. Credit scoring, used for a decade or so in evaluating consumer loans and mortgages, is an automated method that analyzes a large sample of past borrowers in order to calculate the probability that a loan applicant with certain specific characteristics will default.
Proponents of credit scoring for small business loans offer several reasons why the technique may increase credit to LMI areas. First, credit scoring is less costly to both the borrower and the lender than traditional underwriting methods that require time-consuming review of credit reports and financial statements by loan officers. Second, because small business credit scorecards typically weight considerations about the character of a firm's principal, credit scoring could boost the amount of credit available to small businesses in LMI areas if business principals have good credit histories. Finally, credit scoring is a more objective method of underwriting and is thus less likely to produce illegal discrimination.
Those who are skeptical about credit scoring's effect on small business lending in LMI areas argue that scoring will limit the availability of credit. These skeptics assert that credit scores are likely to be unfair because LMI borrowers were underrepresented in the samples of past applicants used to construct the scoring models. If the data samples did not include significant numbers of LMI borrowers and LMI applicants have different characteristics than other borrowers, the scorecards may not accurately reflect the propensity of LMI applicants to repay their loans.
Critics of credit scoring are also concerned that, in assessing small business loans, banks will use scoring as a substitute for having relationships with the businesses. This practice could put LMI businesses at a disadvantage since these firms may rely on a relationship with a lender to overcome unfavorable perceptions of businesses in LMI areas. This relationship is especially important for firms that do not have formal business plans or audited financial statements typically used in traditional underwriting of commercial loans.
Atlanta Fed Study Looks at Scoring vs. Nonscoring
Recent research by Michael Padhi, Lynn Woosley and Aruna Srinivasan of the Federal Reserve Bank of Atlanta explores the impact of credit scoring on small business lending in metropolitan statistical areas (MSAs) in Alabama, Florida, Georgia, Louisiana, Mississippi and Tennessee. The researchers used a data set containing community, demographic, small business, small business loan, branch location and deposit information as well as the results of a survey on banks' use of credit scoring.
Their model controls for the influence of a number of factors, such as total businesses, housing units, lender branches, median income in a community and lender asset size. The researchers try to determine whether there is any significant difference in small business loan originations between low-income (less than 50 percent of MSA median household income), moderate-income (50 to 80 percent of MSA median household income), and high-income (greater than 120 percent of MSA median household income) census tracts for scoring and nonscoring institutions.
Controlling for community and bank characteristics, Padhi, Woosley and Srinivasan analyze data on the amount of small business loan originations of each survey respondent bank in communities with various income levels. Their analysis finds that banks that use credit scoring do not lend significantly less to small businesses in low- or moderate-income areas than to small businesses in high-income areas. Nonscoring banks, on the other hand, lend significantly less money to small businesses in low-income areas. The table shows the average difference between the small business loan dollars originated in low- and moderate-income areas vs. high-income areas. For example, if one controls for other relevant bank and community characteristics, a credit-scoring bank that lends $100,000 in a high-income community would lend $12,386 less in a low-income community, a difference that could occur by chance. A nonscoring bank would lend $51,164 less under the same circumstances. (It is important to note that the model shows an association only. The authors did not attempt to identify a causal relationship between credit scoring and lending patterns.)
Another important finding is that the presence of a bank branch in an area has no significant effect on the amount of small business loans made in that area by credit-scoring institutions. For institutions using traditional underwriting, however, branch presence has a strong positive impact on the quantity of lending in an area. This disparity may indicate that credit-scoring banks can make small business loans without a strong relationship with their borrowers and that nonscorers rely more on having a relationship with their small business customers.
Padhi, Woosley and Srinivasan conclude that credit-scoring banks tend to make small business loans equally across areas of all income levels, from low to high. In contrast, banks that do not credit score small business loans lend less to low- and middle-income areas relative to high-income areas. Furthermore, by reducing banks' reliance on branch presence for information gathering and business relationships, credit scoring may allow banks to lend more easily and with less costs to areas outside their branch coverage. Thus, credit scoring may increase the availability of small business credit or improve the terms on which that credit is offered by increasing the number of competitors lending in a given area.
|The Effect of Tract Income on Small Business Lending|
|Average Loan Originations||Scoring Lenders||Nonscoring Lenders|
|Low-Income Minus High-Income||-$12,386||-$51,164*|
|Moderate Income Minus High-Income||-$9,923||-$33,595|
|Note: The table shows the average small business loan originations in tracts of a given income level minus the average small business loan originations in high-income tracts. Only the difference in originations between low-income and high-income tracts for nonscoring lenders is statistically significant. Census tract income data are from the U.S. Census Bureau.
*Significant at the 0.05 level