The aim of my research is to examine issues relating to the supply of credit to small and medium sized enterprises (SMEs) using a unique UK dataset containing loans and overdrafts from a major UK bank to its small business clients from 1998 until 2000. With this research aim of investigating the supply of credit to SMEs in mind, I constructed several application scorecards that used the information generated from over 7,000 first time applications by business start-ups. The aim of these scorecards was to predict the risk of default of these businesses at least 6 months later using all in-house information about the borrowers’ credit histories. Additionally, I investigated the difference in interest margins between first-period borrowers and applicants for credit who applied in subsequent periods. I also estimated the difference in loan acceptance rates between borrowers with and without pre-existing entrepreneur-bank relationships in order to establish how important relationships are in reducing risk and influencing the likelihood that a borrower will receive finance. In a final empirical part, I investigated the difference in the collateral requirements that the bank demanded from new, small business borrowers compared to the terms that were granted to established business borrowers. My main conclusion is that small businesses are ‘informationally captured’ by the bank i.e. are unable to transfer to a competing bank for subsequent loans, once the first lending period has elapsed. This inference is based on findings where as the level of information about the borrower increases, so also does the cost to the borrower of his finance in terms of interest margin and collateral. My study is the first to use a relatively large scale UK dataset to estimate the probability of default for business start-ups.