Development of a Telematics-Driven Usage-Based Motor Insurance Pricing Engine for India

Objective: To design and prototype a data-driven engine that calculates customized motor insurance premiums in India using real-time telematics and behavioural data.

Problem & Context: Traditional motor insurance in India relies on static parameters like age, vehicle type, and claim history, failing to reward safe driving and discouraging risky behaviour. The rise of connected vehicles and affordable telematics solutions opens the door to usage-based insurance (UBI), which personalizes premiums based on individual driving patterns. However, Indian insurers face challenges in integrating telematics data, pricing accurately, and convincing regulators and customers of its fairness.

Approach & Methodology: The team will conduct domain research on regulatory frameworks, customer adoption barriers, and telematics hardware options in India. They will source real or simulated telematics datasets (e.g., from IRDAI sandbox projects or open mobility datasets), identify relevant features (speeding, braking, distance, time of day), and develop statistical or machine learning models to compute risk scores and dynamic premiums.

Deliverables & Analysis: Deliverables include a data pipeline to process telematics feeds, a pricing engine prototype (Python or Excel), scenario analyses comparing traditional and usage-based pricing, and a business report evaluating regulatory, ethical, and business model implications for Indian insurers.

Business Impact & Decision: The project informs insurers' decisions on UBI product design, actuarial pricing, and market rollout, potentially improving risk selection, customer retention, and profitability while promoting safer driving in Indian roads.