The Revolving Credit Behavior Modeling project analyzes revolving credit to facilitate flexible access to funds within a credit limit, assisting financial institutions in setting accurate pricing strategies by addressing risk factors like inflation and interest rates.

Interest Sensitivity (IS) Gap–based IRRBB model to analyze Net Interest Income (NII) impact under upward and downward interest rate shocks, implemented in Python with FRM-aligned methodology.

Python implementation of a leverage-adjusted Duration Gap model to estimate Economic Value of Equity (EVE) sensitivity under interest rate shocks, aligned with FRM and IRRBB methodology.

Interest rate sensitivity and liquidity stress test model built in Excel to analyze the impact of parallel rate shocks on net interest income and cash position. The model applies scenario analysis with clearly defined assumptions to provide a transparent framework for understanding interest rate and liquidity risk exposure.