Team Member Credit Risk Modelling

YES BANK; Mumbai; On-site; INR 1,500,000 - 2,000,000; Full time

Job summary

YES BANK is looking for an Assistant Vice President (AVP) in Credit Risk Modelling to develop and monitor Internal Rating Models and Expected Credit Loss (ECL) models under IFRS 9 / Ind AS 109 frameworks. Ideal candidates will have 7–8 years of experience in credit risk analytics and strong expertise in statistical modelling and stakeholder management.

The role involves close collaboration with finance and risk teams while ensuring compliance with regulatory standards. Proficiency in analytical tools like SAS, SQL, Python, and R is essential.

Qualifications

• 7–8 years of experience in Credit Risk Modelling within a Bank or NBFC.
• Strong understanding of Internal Rating Models and IFRS 9 / Ind AS 109.
• Hands-on experience in PD, LGD, EAD, scorecards, or rating models.

Responsibilities

• Support development and maintenance of ECL models under IFRS 9 / Ind AS 109.
• Monitor model performance and recommend enhancements.
• Collaborate with teams for ECL methodologies implementation.

Skills

Credit Risk Modelling

Statistical Modelling

Stakeholder Management

Analytical Skills

Regulatory Compliance

SAS

SQL

Python

R

Education

MBA / CA / FRM / CFA / Master’s in Statistics or related discipline

Tools

SAS

SQL

Python

R

Job description

Job Summary

Team Member – Credit Risk Modelling will be responsible for the development, enhancement, implementation, and monitoring of Internal Rating Models and Expected Credit Loss (ECL) models under IFRS 9 / Ind AS 109 frameworks for wholesale portfolios. The role requires strong expertise in credit risk analytics, statistical modelling, regulatory compliance, and stakeholder management within a banking or NBFC environment. The candidate should possess 7–8 years of relevant experience in credit risk modelling, with hands‑on exposure to Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), scorecards, internal rating frameworks, and ECL implementation.

Key Responsibilities

• Support development and maintenance of Expected Credit Loss (ECL) models under IFRS 9 / Ind AS 109 framework.
• Implement staging assessment methodologies, macroeconomic overlays, SICR frameworks, and forward‑looking adjustments.
• Monitor model performance and recommend enhancements based on portfolio behavior and economic trends.
• Collaborate with finance, risk, and business teams for smooth implementation of ECL methodologies within the Bank/NBFC systems.
• Support provisioning calculations, management reporting, and audit/regulatory requirements.
• Perform data extraction, cleansing, transformation, and analysis using large datasets from multiple source systems.
• Analyse portfolio trends, credit behavior, migration patterns, and default characteristics.
• Conduct statistical analysis and model diagnostics using SAS, SQL, Python, R, or similar analytical tools.
• Prepare dashboards and analytical reports for senior management and risk committees.
• Ensure compliance with RBI guidelines, Basel framework, IFRS 9 / Ind AS 109 standards, and internal model governance policies.
• Prepare model documentation, methodology papers, validation support documents, and regulatory submissions.
• Support internal audit, model risk management, and regulatory inspection requirements.
• Work closely with Risk, Finance, Business, IT, and Model Validation teams for implementation and monitoring activities.
• Present model methodologies, assumptions, and performance outcomes to senior stakeholders and committees.
• Coordinate with cross‑functional teams to ensure timely execution of model‑related initiatives.

Required Skills & Qualifications

• 7–8 years of experience in Credit Risk Modelling within a Bank or NBFC.
• Strong understanding of Internal Rating Models, Basel regulations, and IFRS 9 / Ind AS 109 ECL framework.
• Hands‑on experience in development/implementation of PD, LGD, EAD, scorecards, or rating models.
• Good understanding of staging assessment, SICR, macroeconomic overlays, and provisioning methodologies.
• Strong analytical and statistical modelling skills.
• Proficiency in SAS, SQL, Python, R, or similar analytical tools.
• Experience in handling large datasets and performing quantitative analysis.
• Excellent communication and stakeholder management skills.
• Ability to independently manage projects and interact with senior management.

Preferred Qualifications

• MBA / CA / FRM / CFA / Master’s degree in Statistics, Mathematics, Economics, Finance, or related quantitative discipline.
• Experience in model validation or regulatory interaction will be an added advantage.
• Exposure to wholesale and retail credit risk portfolios preferred.

Role: Assistant Vice President (AVP) – Credit Risk Modelling / IFRS 9 & Internal Rating Models