Quantifying Credit Risk in Lending Industry: A Monte Carlo Simulation Approach

The loan data simulated with Monte Carlo approach and analyzed in the research work provides valuableinsights into the borrowers’ financial positions and loan performance. Debt-To-Income ratio (DTI) was calculated and we identified 141 (57.8%) loans that were at high risk of default. We then adopted a risk-based pricing (RBP) to mitigate the risk of default by assigning higher interest rates to riskier loans by taking into consideration some parameters like credit score and risk premium. The analysis revealed that a higher DTI is associated with a higher risk of default, and a higher RBP is associated with a higher interest rate. Therefore, it is essential to use these metrics when assessing loan applications to ensure a healthy loan portfolio. This research can be used to inform loan officers, risk analysts, and other stakeholders involved in the lending process.