• Performs end to end validation of various PPNR models catering to the Bank’s Markets, Private Bank & Retail Bank businesses.• Validation activities include: - Testing of model methodology, modelled and non-modelled assumptions through various statistical tests and model replication.- Incremental tests by developing and testing challenger models to test the validity and stability of the selected models.- Performance monitoring of models through back testing by comparing the… Show more • Performs end to end validation of various PPNR models catering to the Bank’s Markets, Private Bank & Retail Bank businesses.• Validation activities include: - Testing of model methodology, modelled and non-modelled assumptions through various statistical tests and model replication.- Incremental tests by developing and testing challenger models to test the validity and stability of the selected models.- Performance monitoring of models through back testing by comparing the model forecasts with actuals.- Stress testing by analysing the model and portfolio behaviour under various stress & non stress scenarios.- Research and provide incremental techniques and tools to streamline, automate and enhance the validation process and requirements to meet regulatory requirements and suggestions to improve model performances.• Received Silver and Gold awards for key contributions in validations of critical models and enhancement of validation process. Show less

• Works on a team responsible for Model Validation in the field of Model Risk Management for banks.• Performs comprehensive review & analysis of various statistical models (e.g.: Logistic Regression, Linear regression, Gradient Boosted Tree, etc.) used for PD-LGD estimation, Expected Loss forecast, Marketing & provide recommendations to client about model improvements.• Analysis includes model methodology & input data review through statistical tests & metrics and model performance… Show more • Works on a team responsible for Model Validation in the field of Model Risk Management for banks.• Performs comprehensive review & analysis of various statistical models (e.g.: Logistic Regression, Linear regression, Gradient Boosted Tree, etc.) used for PD-LGD estimation, Expected Loss forecast, Marketing & provide recommendations to client about model improvements.• Analysis includes model methodology & input data review through statistical tests & metrics and model performance monitoring.• Using SAS, Excel, MS Word for data analysis and reporting.• Training Project: Case Study of PD estimation and Credit Risk Rating of a bank portfolio using Markov Chain model Show less