Britam Leverages AI to Settle Motor Claims in Two Hours

Britam General Insurance has unveiled an AI-powered drive-through claims settlement facility that processes and pays motor claims within two hours, a sharp reduction from the five-day industry standard that has long frustrated Kenyan motorists.

The Britam AI Motor Assessment Service, located at Britam Centre in Nairobi, was developed by BetaLab, Britam’s innovation hub.

It targets comprehensive motor insurance policyholders whose vehicles have sustained minor damage. Upon arrival at the assessment centre, a customer’s vehicle is photographed and assessed via AI in approximately 15 minutes.

A digital claim form is then sent directly to the customer’s phone for completion, eliminating the traditional and cumbersome paper-based process of filling, scanning and submitting physical documents.

The completed form is reviewed internally within 30 minutes, and settlement, whether by direct bank transfer, M-Pesa, or a repair authority from Britam’s panel of garages, follows within an hour.

The stated end-to-end target is two hours from arrival to resolution.

James Mbithi, CEO of Britam General Insurance, said the service marks a fundamental shift in how the company delivers on its insurance promise.

“Today, five working days is not good enough for our customers. We have launched a capability that assesses accident vehicles using AI and pays the customer within two hours.

In the future, we will be looking at how to scale this up so that a customer can do it at the scene of the accident, wherever they are.”

Mr Mbithi added that the AI platform enhances precision in damage analysis beyond the capability of the human eye, while simultaneously providing the data-backed assessments needed to reduce disputes between the insurer and policyholders.

Fraud has historically been a drain on the motor insurance segment. According to data from the IRA, insurance firms turned down 22,364 compensation claims worth Ksh 658.9 million in the first quarter of 2025 alone, a portion of which involved suspected fraud and improper documentation.

Britam says its platform addresses this vulnerability through three integrated AI models:

• A vehicle object detection model that validates image authenticity and identifies the correct side of the vehicle being photographed;
• A damage detection model that uses computer vision to classify damage type, severity and affected components;
• A price discovery engine that aggregates real-time data from parts suppliers and repairers to generate localized cost estimates.

Together, these models reduce the scope for manipulated photographs, inflated repair quotes and inconsistent assessments, the three most common vectors for motor claims fraud in Kenya.

The digitization of claims processing is a core pillar of Britam’s broader technology strategy, noting that it has operated a structured data-driven assessment framework for over five years that tracks parts prices and informs assessor decisions, a foundation on which the AI layer now sits.

For the moment, the service is confined to vehicles that are driveable and have suffered minor damage and is available only to holders of comprehensive motor policies.