Many banks provide supply-chain finance solutions that might include insurance services that further mitigate trade risk such as the default of suppliers. This study proposes the development of an insurance model that uses the Black-Scholes-Merton (BSM) Model for default prediction and risk pooling management techniques as a way to reduce the risk due to supplier bankruptcy and estimate an insurance premium that banks can use to charge this service to their customers. In order to demonstrate the use of the proposed insurance model, a sample of companies is selected from the New York Stock exchange and data for historical stock prices from the Center for Research in Security Prices database is collected in order to calculate the probability of bankruptcy of a sample of suppliers from different industries by using the BSM model. A Monte Carlo simulation to simulate the impact on risk and expected losses on the number of insurance policies sold is implemented with the use of simulation software. The results show that the simulation is useful to estimate the
number of sold policies required in order to reduce the risk to a minimum level and predict with a high level of certainty the losses due to bankruptcy of suppliers.