Design and Implementation of Automated Claims-Triage and Settlement Workflow for Indian...

Objective: To develop an end-to-end automated workflow that streamlines claims triage and settlement, reducing processing time and fraud in Indian general insurance operations.

Problem & Context: Indian general insurance companies face high volumes of claims, manual triage delays, and frequent fraud attempts, leading to increased operational costs and customer dissatisfaction. There is a growing need for automation to improve efficiency, accuracy, and transparency, especially considering regional and rural penetration challenges.

Approach & Methodology: The team will research current claims processes in India, map workflow pain points, and collect sample claims datasets (from IRDAI, Kaggle, or synthetic data). They will design decision-rule engines and machine learning models for triage (fraud detection, claim type classification) and rapid settlement, integrating with digital document verification and notification systems.

Deliverables & Analysis: Deliverables include a process flowchart, requirements document, a working prototype (dashboard/app), ML model performance metrics, and a business impact analysis. The prototype will demonstrate end-to-end triage, automated fraud scoring, and settlement simulations, validated with test cases.

Business Impact & Decision Informed: The solution informs operational leaders about the potential for cost reduction, faster claim settlements, reduced fraud, and improved NPS (Net Promoter Score), supporting decisions on technology adoption and digital transformation strategies in Indian insurance firms.