Website:
yes.bank.in
Job details:
Job Title
Team Member – Credit Risk Modelling
Role Objective
To support the development, maintenance, and validation of internal credit risk rating and scoring models. The role ensures models remain robust, accurate, and compliant with regulatory requirements, enabling effective credit risk management and decision-making.
Key Responsibilities
- Model Development & Enhancement
- Design and develop internal credit rating models, scorecards, and risk measurement tools across portfolios.
- Incorporate statistical, econometric, and machine learning techniques where applicable to strengthen predictive power.
- Ensure models align with business requirements, regulatory expectations, and industry best practices.
- Model Validation & Performance Monitoring
- Conduct back-testing, benchmarking, and performance evaluation of models to ensure accuracy and reliability.
- Monitor model behavior and recommend recalibration or redevelopment as required.
- Document model assumptions, methodologies, and validation outcomes in line with governance standards.
- Model Maintenance & Compliance
- Ensure models are kept up-to-date with changing macroeconomic conditions, portfolio characteristics, and regulatory guidance.
- Assist in periodic reviews and audits of models to ensure compliance with RBI/ Basel/ Ind AS 109 requirements.
- Support preparation of regulatory submissions and responses to audit queries.
- Systems & Process Support
- Work on integration of credit risk models into internal systems and workflows.
- Coordinate with IT and data teams to ensure smooth implementation and automation of models.
- Contribute to process improvements and digital initiatives within the modelling function.
- Stakeholder Engagement
- Collaborate with Risk, Business, Finance, and Compliance teams to ensure effective application of models in decision-making.
- Provide analytical support, insights, and training to relevant stakeholders on credit risk models.
Key Skills & Competencies
- Strong understanding of credit risk, rating models, and regulatory frameworks (Basel, RBI, Ind AS 109/ IFRS 9).
- Proficiency in statistical techniques, econometrics, or machine learning methods.
- Hands-on experience with data analysis tools (e.g., SAS, R, Python, SQL).
- Strong analytical, problem-solving, and quantitative skills.
- Excellent documentation, communication, and collaboration abilities.
Qualifications & Experience
- Postgraduate degree in Statistics, Economics, Finance, Mathematics, Data Science, or related field.
- 2–5 years of experience in credit risk modelling, scorecard development, or related quantitative risk management roles.
- Prior exposure to regulatory risk model governance and validation desirable.
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