Lead - Risk Management-Delhi NCR
- Delhi
- Permanent
- Full-time
- Analysis and visualization of risk factors using database and analytics tool like SQL, Python/SAS, Power BI, Excel
- Responsible for enhancing and performing Internal Capital Adequacy Assessment Process (ICAAP) and prepare comprehensive ICAAP document for presentation to Board in line with Basel / RBI norms. Keep ICAAP policy updated in line with regulatory guidelines.
- Perform Stress Testing on material risks in line with RBI guidelines / Basel norms and Stress Testing Policy. Develop & maintain Stress Testing Framework
- Credit Loss Modelling for the Corporate Finance Portfolio for ECL Provisioning
- Maintain credit Models on Basel/IFRS 9 (PD, LGD, EAD) etc. for ECL (Expected Credit Loss) Calculations
- Develop and maintain 'Risk-Based-Pricing' and 'RAROC' models for Corporate Finance portfolio
- Query large data sets to draw insights from loan portfolio data to detect early warning indicators
- Extensive data mining to monitor the changes in trends, outlook and review the portfolio quality and performance
- Data Analysis and performance Tracking/Portfolio Management for the Corporate Portfolio
- PD Modelling with Flow rates and Linear Regression, and Vasicek method
- Perform Stochastic Stress Testing using Regression, Vasicek, CIR models
- Perform portfolio analytics - Vintage, Waterfall, Through the door analysis etc.
- Perform Portfolio deep-dive to identify emerging trends; contribute towards improving portfolio quality and reducing non-performing loans
- Regulatory Report filing on Monthly/Quarterly/weekly basis
- Design Guardrails for each product and monitor them for sensing & sending Early Warning Alerts
- Monitor Macro/Micro/High Frequency indicators; keep a close monitoring on movement of these indicators and perform impact assessment.
- Post-Graduate (FRM / CFA preferred)
- Min 10+ Years of Work Exp.
- Understanding of Basel norms/IFRS 9 (PD, LGD, EAD), IND AS9, ICAAP, RAROC, Regulatory, Financial Concepts. Statistical Concepts (Econometrics), Data Science and Machine Learning algorithms,