Pratimesh Singh

• Transformed the use of Probability of Default Model, by including stimulus information, to lower errors from 70% to under 10% • Redesigned Stress-Testing analysis to include Inflation Impact Assessment, which also helped 10 other validation projects • Modernized the Auction Price Model, to ensure the model has better Sensitivity to Macroeconomic factors, especially on COVID data • Designed Model Policy Forum, to keep the Bangalore team updated with the latest Federal Guidelines for optimizing Model Risk

• Saved $100k+ and 40+ man-hours monthly, by developing an automated system to identify wrong Tax and Excise transactions • Reduced under-utilization of trucks (logistics) by 40%, using optimization algorithm to combine orders and reduce empty runs • Developed scalable Machine Learning based framework to determine Credit Risk and Credit Limit for Customers in Netherlands