Manager - Analytics (ECL) - Mumbai - Lodha (I-Think Techno Campus) - JM
1 week ago
Job Brief:
We are seeking a detail-oriented and analytical Credit Risk Analyst to join our team. The ideal candidate will specialize in credit risk modelling, particularly in the areas of Expected Credit Loss (ECL) under CECL/IFRS 9, and the development and validation of PD (Probability of Default) and LGD (Loss Given Default) models. This role is critical in supporting the organization's credit risk strategy and ensuring compliance with regulatory standards.
Key Responsibilities:
Credit Risk Assessment & Modelling
1. Interact with senior management for driving Business growth and optimizing risk though analytical solutions
2. Use sophisticated statistical techniques to design advanced analytical scorecards for customer acquisition, customer lifecycle management and collections
3. Credit Risk Analytics with prime exposure to Ind AS, ECL, BASEL and IFRS9 Modelling. Maintain documentation and controls in line with internal and external audit standards
4. Development, validation and Implementation of credit risk models – ECL: PD, LGD estimation, CECL - forward looking PD estimation using Time Series, OpVar Calculation, recovery estimation, portfolio valuation (buyouts, sell-down).
5. Compile and analyse macroeconomic and borrower-specific data for model inputs.
6. Analyse financial data and borrower behavior to assess creditworthiness
7. Portfolio Analysis and deep dive on various segments/cohorts
8. Manage Bureau relationship and leverage it for market trends/insights
9. Data augmentation through external/Alternate Data providers partners for better scoring
10. Use of Machine Learning algorithm for advanced analytics
11. Collaborate with business users for implementation and monitoring of scorecards/solutions and impact on business and risk
12. Implementation of analytical solutions through IT platform
Cross-functional Collaboration
• Work with Risk, credit, finance, and data teams to align risk models with business needs.
• Provide insights and recommendations to optimize credit decisions
Qualifications:
• Bachelor's or Master's degree in Finance, Economics, Statistics, or related field.(From premium Institutes like DSE, MSE, ISI, IIT)
• Proficiency in statistical software (e.g., SAS, R, Python) and Excel.
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