Role Description
To undertake key activities pertaining to data and analytics for the LAP LOB including trends in disbursals & portfolio for identification of strengths in the portfolio as well as early delinquency indicators in order to help build a strong and healthy Corporate Finance book.
Key Responsibilities:
1. Portfolio Performance Analysis & Reporting:
o Assist in monitoring portfolios on daily/weekly/monthly basis to maintain risk metrics at desired levels by continuously analysing, identifying the high-risk segment from portfolio.
o Regularly monitor and report portfolio performance to stakeholders, providing critical information that supports strategic decision-making across departments such as sales, credit, operations, and senior leadership.
o Generate various metrics & tracking’s for assessment of the through the door quality, approvals and performance across various channels
o Prepare insightful decks and dashboards to analyze and track trends in the SME-Finance portfolio, including disbursals, performance, and other key risk indicators.
2. Portfolio Reviews:
o Support in conducting portfolio review meetings with stakeholders, following a defined operating rhythm to evaluate the health of the portfolio, identify potential risks, and recommend mitigation strategies.
3. Data Management & Integrity:
o Ensure the accuracy, standardization, and integrity of data used for portfolio management activities, making certain that data is clean, reliable, and ready for further analysis.
4. Advanced Portfolio Analytics:
o Utilize advanced portfolio analytics techniques to analyze portfolio performance and risk, including Vintage Curves, Portfolio at Risk, Early Warning System (EWS), Bureau Scrub Analysis, Flow rates, Bounce Analysis, Loss Forecasting, and Stress Testing.
o Apply analytical insights to identify trends and recommend strategies to optimize portfolio performance and mitigate risks.
o Deep dive with data and assist in recommending policy changes and decision making around risk & opportunities for the businesses
5. Data Handling & Statistical Analysis:
o Use large data-handling software (e.g., SQL) and statistical software (e.g., SAS, Python, R) to process, analyze, and visualize portfolio data at scale.
o Ensure data is utilized effectively to perform in-depth statistical analysis and provide actionable insights.
6. Regulatory Reporting:
