Determination of Credit Insurance Premium Due to Default Using the Black-Scholes-Merton Model
Keywords:
Default Risk, Credit Insurance, Determination of Premiums, Monte Carlo simulation, Black-Scholes-Merton model.Abstract
Banks are vulnerable to the risk of bad credit or default because customers are unable to pay their debts. Risks that may occur in the future can be in the form of unexpected events and can be experienced by anyone, causing the loan to not be fully repaid. Therefore, it is necessary to have insurance to overcome risks due to default in protecting oneself from the risk of unexpected events, namely credit insurance. This study aims to calculate the premium price using the Black-Scholes-Merton model approach. The data used is arrears data of customers PD. Bank Perkreditan Rakyat (BPR) Artha Sukapura in 2003-2020. The data is compiled into a cumulative relative frequency distribution table, resulting in a number of random numbers. Based on the cumulative relative frequency distribution table, data simulation was determined using Monte Carlo. Based on the results of the analysis, the simulation data obtained by the standard deviation are relatively stable and lognormal distributed. Then pricing is done to determine the premium price from the sample data. From the results of the calculations in this study, a premium value of  was obtained for arrears of  with a loan of .References
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