Bank behavior based on internal credit ratings of borrowers

This study examines the relation of bank loan terms like interest rates, collateral, and lines of credit to borrower risk defined by the banks' internal credit rating. The analysis is not restricted to a static view. It also incorporates rating transition and its implications on the relation. Money illusion and phenomena linked with relationship banking are discovered as important factors. The results show that riskier borrowers pay higher loan rate premiums and rely more on bank finance. Housebanks obtain more collateral and provide more finance. Caused by money illusion in times of high market interest rates loan rate premiums are relatively small whereas in times of low market interest rates they are relatively high. There was no evidence for an appropriate adjustment of loan terms to rating changes. But bank market power represented by a weighted average of credit rating before and after a rating transition serves to compensate for low earlier profits caused by phenomena of interest rate smoothing. Klassifikation: G21

Number of bank relationships : an indicator of competition, borrower quality, or just size?

In this study the firms' choice of the number of bank relationships is analyzed with respect to influential factors like borrower quality, size and the existence of a close housebank relationship. Then, the number of bank relationships is used as a proxy to examine if bank competition is reflected in loan terms. It is shown that the number of bank relationships is foremost determined by borrower size and the existence of a housebank relationship. Loan rate spreads are not effected by the number of bank relationships. However, borrowers with a small number of bank relationships provide more collateral and get more credit. These effects are amplified by a housebank relationship. Housebanks get more collateral and are ready to take a larger stake in the financing of their customers

Empirical analysis of credit relationships in small firms financing : sampling design and descriptive statistics

Despite the relevance of credit financing for the profit and risk situation of commercial banks only little empirical evidence on the initial credit decision and monitoring process exists due to the lack of appropriate data on bank debt financing. The present paper provides a systematic overview of a data set generated during the Center for Financial Studies research project on "Credit Management" which was designed to fill this empirical void. The data set contains a broad list of variables taken from the credit files of five major German banks. It is a random sample drawn from all customers which have engaged in some form of borrowing from the banks in question between January 1992 and January 1997 and which meet a number of selection criteria. The sampling design and data collection procedure are discussed in detail. Additionally, the project's research agenda is described and some general descriptive statistics of the firms in our sample are provided