An AI-driven Approach to Enabling Low Touch Claims Processing

Business Objective

Our client, a leading US-based auto insurance provider, wanted to simplify and accelerate claims resolution by reducing human touch. Specifically, the client intended to use AI to assess vehicle damage and estimate repair cost from the photos shared by the claimants.

To meet the stated objective, the client wanted to

Perform a discovery to identify the most impactful image analytics use cases that can deliver measurable business impact
Create a roadmap that outlines the execution approach, data requirements, and the required technology stack

Solution Methodology

Identified three primary drivers of auto repair costs
- Damage category: 12 distinct categories identified, including dents, scratches, cracks, stains, broken and missing parts
- Damage severity: created a rating scale to ascertain moderate to significant damage severity
- Body style: Sedan, Pickup, SUV
Recommended high-impact image analytics use cases for execution by selecting those that are most addressable based on body style and damage category
Developed a blueprint that outlines AI & engineering skills and the conceptual technology architecture required to address the key challenges below
- Creating high quality annotated data
- Accounting for variations in image quality

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An AI-driven Approach to Enabling Low Touch Claims Processing

Business Objective

Challenges

Solution Methodology

Business Impact

An AI-driven Approach to Enabling Low Touch Claims Processing

Business Objective

Challenges

Solution Methodology

Business Impact

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