About Client:

Our client is one of the leading financial services platforms offering affordable financial products through a technology-driven lending ecosystem.

Job Description:

We are looking for a Risk Analytics professional with strong experience in Credit Risk Modeling, Predictive Analytics, Underwriting Strategy, and Portfolio Risk Analytics for unsecured lending products. The role involves developing and monitoring risk models, enhancing underwriting policies, analyzing portfolio performance, and delivering data-driven insights to optimize credit decisioning and portfolio quality.

Responsibilities:

- Develop, validate, and enhance credit risk models and scorecards to evaluate customer risk, underwriting effectiveness, and portfolio performance.

- Build and monitor predictive models using statistical and machine learning techniques to improve credit decisioning and portfolio quality.

- Monitor model performance using statistical performance indicators and recommend recalibration or policy enhancements where required.

- Analyze portfolio performance, customer cohorts, and borrower segments to refine underwriting policies and risk strategies.

- Monitor portfolio performance across delinquency buckets (30+, 60+, 90+ DPD), vintages, and customer segments, and provide actionable insights to optimize credit policies and minimize risk exposure.

- Develop and optimize collections strategies using customer segmentation, DPD bucket analysis, geography, and product performance.

- Identify roll-forward trends and early warning signals through portfolio and behavioral analytics to proactively mitigate credit losses and NPA slippages.

- Collect, manage, and analyze data from multiple sources to support risk analysis and business decision-making.

- Design and maintain portfolio monitoring dashboards covering delinquency, flow rates, recoveries, and portfolio performance metrics.

- Analyze portfolio risk metrics including delinquency trends, Expected Credit Loss (ECL), recovery efficiency, and other key risk indicators.

- Prepare and present MIS reports, portfolio insights, and business recommendations to senior management.

Technical Expertise:

- Strong proficiency in SQL and Microsoft Excel.

- Experience with Python or R for statistical analysis and predictive modeling.

- Experience with Tableau, Power BI, or similar BI tools.

- Knowledge of statistical modeling or machine learning techniques will be an advantage.

- Experience working with risk analytics platforms or lending management systems is preferred.