Lender evaluations of start-up business prospects

Purpose - The purpose of this paper is to investigate lender evaluations of start-up success in a sample of Finnish firms that are customers of a state-owned financial institution. The database allows the authors to examine how qualitative information, based on the personal history, firm-specific characteristics, subjective credit-analyst evaluations of business prospects, and market position impact firm performance. Design/methodology/approach - The data for this study was collected in 2003 and 2005 from the database of Finnvera, a state-owned financial institution. The authors employed logistic regression in the analyses, using t-test analyses to describe the sample before developing the different models. Findings - The results suggest that the lenders' evaluations of the business prospects at the start are suitable predictors of good performance. However, the determinants of the actual firm performance (at t5) and business prospects (at t0) are, to some extent, different. The results confirm previous findings indicating that humans display fallibility because they have a tendency to overestimate less relevant cues and, conversely, underestimate the more relevant ones. Research limitations/implications - The study data includes only the customers of a state-owned financial institution; therefore, the results cannot be generalized across other financiers. Another constraint relates to the pre-selection bias, since this data excludes information on loan applicants who were rejected, which was not recorded in the lender's files. Practical implications - The findings of this study provide lenders (especially state-owned financiers), policy makers, and entrepreneurs with clearer guidance regarding the important aspects of a firm's period of establishment. For lenders, this may provide a step toward improving the quality of judgments. Originality/value - This paper is one of the few that sheds light on lender evaluations using non-accounting variables in order to examine their ability to predict firm performance, not failure, and to compare it with lenders' evaluation. Another original contribution is that the data consists of the customers of a state-owned financial institution.