Working as a business analyst with renewal and retention teams. Managing data, creating Dashboards and automating their processes. Working on predictive and regression models, helping in taking company’s future decisions and sales planning.Analysing trends in large and complex datasets to enable data-driven business strategies.Data analysis and making new definitions for upsell and cross sell for future.

Fraud & Risk management:Suspicious Agent identification from the historic data, automated the process using Python and ExcelAgent bifurcation in different bands out of 1,80,000 agents basis the risk involved.Fraud and abuse management work was automated to identify the high risk Agents.Predictive modelling: Pridit Score model was created on Python that was integrated in business rule engine forClaims processing.Supervised Machine learning model was created for FAM with an accuracy of 89%.Project Highlights: The model was presented to the officials of Ayushman BharatThe overall loss ratio of Apollo Munich was brought down by 1.3%.For the high risk areas identified, Loss ratio was brought down by 8% & 3% for Gujarat & Nasik respectively.Received Letter of recommendation & Award from the Chief Actuarial of Apollo Munich.