The research group at the Institute for Innovation Research at the University of Waterloo analyzed a group of nearly 4,700 entrepreneurs/owners to isolate the key factors responsible for business survival during the first four years of operations. Adopting additional variables that accurately predict business survival will significantly reduce bank losses for loans granted to startups, say the authors, who believe that loan decision error costs can be reduced by 0.5 to 1.6 percentage points by using a few additional criteria. They argue that this anticipated reduction is significant because error costs range from 2.1 to 4.4 percentage points for start-up loans.
Commercial banks have been criticized for failing to support small businesses during the start-up phase. Banks counter these charges by insisting it is virtually impossible to assess the true business-worthiness of start-up firms. Given the difficulty of assessing business-worthiness, commercial lenders tend to favor appraisals of an applicant's personal creditworthiness over those of the business-worthiness of the start-up. Banks contend that a business loan secured by means of personal assets alleviates anxiety about borrower insolvency. But if a business fails while retaining a fully secured loan, the lender must incur collection costs and must expect that the value of a borrower's secured assets are often lower than when evaluated. A fully secured loan does not ensure, therefore, that a lender will avoid all losses in the event of business failure.
The industry's dependence on assessment of personal creditworthiness continues to limit access to credit for start-up firms unable to secure loans by means of an applicant's personal worth. While the industry's pursuit of fully secured loans seems theoretically justifiable, the practice creates an auxiliary market of "ineligible," yet worthwhile, business risks for banks willing to adopt statistically verifiable models for predicting the success of start-up firms. This auxiliary market is large and remains relatively untapped. There were 819,500 firms launched in the U.S. during 1995 and only about 25% of these start-ups obtained a commercial bank loan. By implementing additional variables when assessing business risk, commercial banks can significantly reduce loan losses when tapping into this market and transform unprofitable lending into profitable lending.
The Current Situation: A Call for Internal Improvements
Assessment models presently employed by banks must be modified to include additional information conducive to a more comprehensive measurement of risk. Adequate assessment of business risk must reflect, then, an appreciation for key entrepreneurial success factors not currently available at most lending institutions. To enhance current credit-scoring models, commercial banks are advised to adopt the following four-step agenda:
* Assemble a team of experts to determine additional factors crucial to improved accuracy of model (three to six months).
* Revise the bank's loan application procedure to accommodate recommendations put forth by team (three months).
* Process applications, grant loans, and collect data. Wait for loans to mature (two to four years).
* Analyze data set, isolate supplementary factors, formulate and implement revised model (six to 12 months).
By pursuing the steps cited above, commercial banks can arrive at more informed appraisals of business risk and, in doing so, can reduce loan losses and error costs. As also indicated above, however, banks can expect to improve lending performance in the domain of small to medium-sized enterprises (SME) only at a considerable cost and a delay of implementation of 36 years. And lenders will likely remain cautious about whether the most germane supplementary success factors are captured in any revised loan-assessment program. Since the costs of modifying assessment procedures are substantial and the benefits are uncertain, the industry has not moved forcefully to improve strategies for assessing business risk. …