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Making Insurance Fraud Detection Smarter with AI
Client Overview
Our client operates in auto insurance, managing a steady stream of accident-related claims and the investigations that follow. Around 500 new accident-related claims arrived each day, and individual cases could involve multiple stakeholders and different forms of information. The client’s fraud review process depended heavily on investigators manually bringing these pieces together. They partnered with us to introduce AI into their insurance fraud detection process, with the goal of giving investigators better signals and a more focused way to identify suspicious claims.
The Challenge
- 500 new insurance claims a day were putting pressure on a largely manual fraud review process.
- It took at least seven days to manually process 2,000 claims, creating a backlog as new claims kept coming in.
- The insurer needed to scale claims operations without having to grow their team at the same rate.
The Solution
We built an AI-based fraud detection solution that adds an automated screening layer to the insurer’s existing claims process. It combines the insurer’s business rules with AI analysis of the information available around each claim, helping investigators identify and prioritize cases that may need a closer look.
- Claims received through the existing external portal are brought into the client’s server for processing.
- An automated job runs at midnight to screen all claims received during the day.
- The solution brings together information such as accident photos, notes, investigation records, conversations, feedback, supporting documents, and raw text.
- The insurer’s existing fraud detection rules are applied alongside the AI-based analysis.
- An LLM analyzes the available information to identify anomalies and patterns that may indicate potential fraud.
- Each claim is given a fraud confidence score, with higher scores indicating a greater potential for fraud.
- Insurance claims reaching the 90% confidence threshold are flagged for further attention. .
- Flagged claims are ranked by their confidence score, giving investigators a prioritized list to work through first.
Business Outcome
By introducing artificial intelligence in fraud detection, the insurer could shift the initial screening burden away from a fully manual process. The solution worked through both structured and unstructured information and helped investigators identify which cases warranted closer attention. This made it possible to handle growing claim volumes with the existing team while creating an opportunity to prevent significant fraud losses. For this insurer, potential fraud across 20 claims meant as much as $260,000 in losses avoided.
From Challenge to Impact, Read the Full Story
Explore the full story of how we built an AI-powered approach to help this insurance company identify claims with stronger fraud signals. Download the Full Case Study Now.
In a dynamic business environment, scalability is crucial. IT services provide the flexibility to scale up or down your resources based on changing business needs. Cloud services, for instance, allow seamless expansion of storage and computational power
Serana Belluci
Product Designer
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