Aniketh Moparthi

Insurance Analytics:

• Closely worked with a fin-med intermediary who aims to revolutionize health insurance industry. They provide advance float payment to providers (clinics) who submit an insurance claim (also called as 837 filing). Advance float amount disbursed is based on a float percent for individual providers, claim risk category, and the Accounts Receivable Days (AR Days) after deducting an interest amount.
• Multiple machine learning algorithms like XG Boost, Gradient Boost, Random Forest, Regression and Ada Boost have been tried to predict the risk score and Risk Category (High, Medium, Low) for a particular claim submission (837).
• XG Boost algorithm has been finalized based on its MAPE 0.257 and adjusted R square 0.8547.
• Developed and deployed tableau-based dashboards to track certain operational and financial KPIs like LOS (length of stay), % of approved claims, denial rate and denial amount by provider.

Retail Analytics:

• Delivered regular Financial reports based on SQL and Excel to L1 group for a CPG client. It enabled them to track Expenses and Profitability at SKU level.
• Profitable SKUs and platforms were given more focus and expenses were rationalized based on our reports.

• Supported staff members in their daily tasks, reducing workload burden and allowing for increased focus on higher-priority assignments.
• Enhanced intern productivity by assisting with project coordination and providing ongoing support.
• Analyzed problems and worked with teams to develop solutions.
• Maintained database systems to track and analyze operational data.

• Elected as Sports coordinator in college annual festival called Manasara.

• 3.9 GPA