MADHU KIRAN GOLLA

Leading analytics for collections/Loss Forecasting/Portfolio Analytics on secured / unsecured lending portfolio of 15 products

Achieved early promotion and given excellent rating for outstanding contribution to projects.

• To prioritize the personal loan accounts based on likelihood of recovery payment from written-off pool
• Utilized outside payment behavior, historical payments, and collections intensity as predictive variables
• Simultaneously used Segmentation & Gradient Boosting model to train the data for better segregation
• Successfully improved month-on-month recoveries by ₹20 million, contributing to a 20% increase.

• Delivered a 3 year credit cost forecast for a portfolio of 15 secured and unsecured lending products
• Assessed 7+ KPIs including Expected Credit Loss & Net Credit Loss basis historical trends & business dynamics
• Implemented scenario testing on risk parameters such as delinquency, flow rates and lifetime recovery rates
• Reduced TAT in model update by ~50%, leveraged VBA macros and SQL queries for data handling.

• Performed stress testing on a ₹450 billion portfolio for capital requirements using the Vasi Check method
• Assessed firm wide credit risk impact on delinquency, default rates, recovery rates and expected losses
• Revamped the framework for Stress testing for quantitative assessment of required regulatory capital
• Managed stakeholders across the organization from Finance, Collections strategy and Policy teams.

• Predicted the probability of a customer defaulting on personal loans within the next 12 months
• Employed logistic regression on 6 years of historical data to analyze default behavior.

• Evaluated non-performing portfolio for a potential pool sale to strategic buyers using a statistical approach
• Assessed risk parameters such as loss rate, lifetime recovery rate and collateral value ratios for valuation.

• Minimize energy requisite for the closed-loop pneumatic conveying system of polymerization unit
• Proposed change from 3 lobe to twin-screw blower with variable speed drive for better energy efficiency
• Pinpointed the use of gamma bend tubes & high radius bends to reduce the pellet degradation at bends
• Estimated a 10% energy reduction through proposed modifications of equipment & operating conditions.