AVP - Credit Risk Management

Role Objective:

As the AVP - Credit Risk Management, you will play a pivotal role in shaping and executing the credit risk strategy for India. You will be responsible for defining credit policies, overseeing underwriting standards, managing portfolio quality, and ensuring that the organization balances aggressive growth with robust risk mitigation. This role requires strong leadership to guide a team of risk professionals and collaborate cross-functionally with Business, Tech, and Analytics teams to optimize risk outcomes across Digital lending portfolios.

Key Roles & Responsibilities:

Policy Formulation & Strategy:

- Formulate, review, and continuously optimize credit risk policies, underwriting frameworks, and risk appetite parameters across various Digital retail lending products like Personal Loan.

- Design and implement end-to-end risk management strategies covering the entire customer lifecycle, including acquisition, portfolio management, fraud prevention, collections, and recovery.

- Use data-driven insights to improve risk selection, risk-based pricing, and loan allocation strategies.

Credit Underwriting & Appraisal:

- Oversee the credit assessment and approval processes, ensuring strict adherence to the established credit policy and regulatory guidelines set by the Reserve Bank of India (RBI).

- Conduct deep-dive credit analysis for expansion/ pull back proposals, and actively participate in internal credit and risk committees.

- Enhance automation and digital underwriting processes by working closely with Product and Engineering teams, aiming to improve turnaround times (TAT) and operational efficiency without compromising risk standards.

Portfolio Monitoring & Analytics:

- Conduct rigorous portfolio analysis and monitor delinquencies at a micro and macro level. Identify vulnerable segments, programs, locations, and profiles.

- Establish and track Early Warning Signals (EWS) to identify signs of stress early and initiate proactive corrective measures.

- Identify emerging risks, concentration issues, and market trends, providing analytical support for internal management reviews.

- Collaborate with the Data Science team to validate, provide inputs for, and optimize risk models (scorecards, PD/LGD models). Create a deep-level understanding of both traditional and alternate data sources for underwriting optimization.

Team Leadership & Stakeholder Management:

- Lead, mentor, and develop a high-performing credit risk team.

- Ensure seamless cross-functional collaboration with Business Heads, Product Managers, Data Scientists, and Product/tech teams to align risk strategies with organizational growth targets.

Required Skills & Qualifications:

Must Have Skills:

- Masters degree or MBA in Finance, Economics, Business, or related fields from a top-tier institution; or professional qualifications such as CA (Chartered Accountant), CFA, or FRM.

- 6 to 10 years of proven experience in credit risk management, policy formulation, and risk analytics within a Bank, NBFC, or Fintech ecosystem.

- At least 2-3 years of Risk team management experience.

- Deep domain expertise in Risk Management about unsecured credit products in the Indian credit ecosystem.

- Familiarity with risk modeling concepts, machine learning techniques (like decision trees), descriptive analysis, and probability distributions to effectively work with risk/ data science teams.

- Demonstrated experience in evaluating both structured and unstructured data to make informed risk decisions.

- Strategic Mindset: Ability to balance business growth objectives with prudent risk management.

- Analytical Thinking: Advanced problem-solving skills with the ability to translate complex business problems into actionable analytical frameworks.

- Communication: Excellent stakeholder management and communication abilities to articulate risk perspectives clearly to senior management and external partners.

Good to Have Skills:

- Fintech or retail/MSME digital lending experience is highly preferred.

- Proficiency with analytical and data mining tools; hands-on experience in SQL, Python, or R is a distinct advantage for working closely with analytics teams.

- Strong understanding of RBI regulatory frameworks, compliance requirements, and Expected Credit Loss (ECL) provisioning standards.