Narrow Results

The bank has the access to hard and soft information about small and medium-sized enterprises (SMEs) in order to manage the informational opacity. We carry out the study about the information and bargaining power between lenders and borrowers. Bargaining power is depicted based on more favorable loan rate. The proxy is regressed on hard information, soft information and other variables. We find out that more favorable hard information (Registered Capital and Proceeds of Sale) increases borrowers' bargaining power in China. We also obtain evidence suggesting that the length of borrowers' business affect the bargaining power.

Entrepreneurial and business skills are generally considered key to microbusiness success, hence to Microfinance Institution (MFI) clients’ loan repayment as well. However, empirical evidence is largely lacking, and where present, it is inconclusive on the importance of these skills for microfinance success. The present paper uses objective MFI loan repayment data to empirically test whether loan repayment rates positively correlate with self-evaluations on entrepreneurial and business skills of loan clients. A survey was conducted among 235 loan clients of uniCredit — an MFI in Ghana. We establish that MFI clients’ self-evaluation of their entrepreneurial and business skills are not related to their loan repayment rates. However, we observe that women repay their loans better than do male microbusiness entrepreneurs, and loan repayment was also better for those entrepreneurs with more than 15 years of business experience.

A framework for measuring and managing the risk of embedded options in non-traded credit is developed. For typical bank clients there is no market information related to their ability to pay (bond or CDS spreads) available. The absence of market information is a key assumption of this paper. In this case, a bank has to rely solely on statistical data to judge the credit quality of a borrower. To value a loan with embedded options like prepayment rights, a model is proposed that combines an interest rate derivatives pricing model with statistical information on default and recovery rates. Using this for evaluating the risk of embedded options in loans, it is shown how the concepts of credit risk management can be applied after defining a suitable concept of risk. It turns out that this modeling framework combines the theories of derivatives pricing and credit risk modeling in the sense that derivatives pricing theory measures the costs for hedging optional components in loans while credit risk modeling measures the risk that these hedging costs turn out to be inadequate. This risk depends not only on the single loan’s risk characteristics but also on the dependence structure and the granularity of the total loan portfolio.