 Antifoam Optimization Project: Optimized product properties for the specific requirement of the customers. Used Data Modeler to find the most interpretable model with high R^2. Used SLSP algorithm in python to optimize the objective function. Used Plotly and SAS JMP for 3d visualization. Anomaly Detection on Procurement Data: Designed an anomaly detection framework to find flaws in historical transaction data: identified ~$3million of mispayment to outside vendors in the last 2 years.

 Project CDMP (Consumer Debt Management Program): Identified loopholes in the regulatory process of CDMP. Designed and automated codes to extract weekly reports of mismatched data. Worked with business team and data engineers to reduce these loopholes - prevented ~2% wrongly defaulted customers and defaulted 1% wrongly enrolled customers. Key MIS reports: Developed 10+ MIS capabilities to assist senior leadership in taking business decisions and improving collection effectiveness. Automation: Used Multidimensional Expression (MDX) to automate 8+ Excel-based reports, saving 20+ man-hours per week.

 Life Insurance Customer Base: Identified premium customers not enrolled in life insurance product and the reasons behind it. Designed a framework to calculate the minimum amount could be given to these customers with minimal documentation: increased the sale of the product by 20-25%. Late Fee Enhancement: Designed a new fee framework and simulated its impact on bank’s earnings. Assigned late fee fine to customers according to their month end balance - 10% customers were prevented to pay unreasonable late charge on their accounts.  Engagement analysis: Clustering and segmentation of customers based on demographics and product holding to increase customer engagement and PPC (products per customer).