Subhadeep Saha Email and Phone Number

•Developed bounce prediction model for bucket 0 customers - The model was developed to predict the bucket zero customers who are going to be delinquent in the next collection cycle.• Automation of ECL calculation - The automation of the ECL calculation was done using Python based and VBA based framework. The main objective was to reduce the TAT and reports can be easily generated from different cohorts.• Calculation of ECL for unsecured product portfolio, giving business insights to the business teams for taking preventive measures. The reports are reported to the CXO's of the organization.• Developed VBA based Blackbox Utility - One click calculation of eligible dealership selection who will part of underwriting. Though the main objective of this development was to protect the customer level information of the company and to calculate the eligible loan amount of the dealers.• Development of Collection Health Report - Collection Health report was developed to monitor the collection performance of collection branches, so, that the resource allocation can be done optimally, and collection can be improved. This framework has been developed using Python and automated end to end.• Worked on Automation of Collection Incentive Calculations - This development is a process excellence project, where our main objective was to reduce the TAT and to convert the complicated Excel calculation into a python-based framework.• Analytics for Supply chain Finance - In Supply Chain Finance business, specifically for channel financing, to analyze the behavior of the client, I have developed an early warning signal framework, and it can be scalable in similar kind of business. It helps the business to take decision before lending in near future and help to filter out the bad customers from the book.• Deep analytical research into a business problems as requirement comes from business.• Data preparation, report generation, BAU responsibilities.

• Prepare monthly and quarterly risk and portfolio reports.• Develop presentations detailing trends and forecasts for senior management. • Forecasted and modeled future credit and risk trends.• Completed monthly Credit Watch Report.• Monitored data integrity and made corrections.1. Development of Predictive Risk Model to predict bounce % for the upcoming EMI Cycles - This project was to develop a predictive model using Historical data in order to predict the behaviour of the existing customers. It helped the management to understand the upcoming loss from EMI bounce. It also helped in increasing manual collection and reducing the bounce percentage. Model also provided the insights on foreclosure customers and loan cancelled customers to the management.2. 100% integration of Tableau dashboards- Created interactive dashboards on this project. Developed new tableau dashboards for different operational teams from the business viewpoint it helped to analyze the gaps, granularity, to analyze the operational faults, easy to overcome the problems, easy to take decisions.