Insurers face a huge volume of claims, most of which are still assessed manually, leading to long backlogs and a poor customer experience. More seriously, claims files typically contain health data and personal information — among the most strictly protected data categories under personal data protection laws such as the EU GDPR — making processing through a public cloud platform a significant legal risk.

Another direct financial issue is insurance fraud and abuse — industry estimates put it at 5–10% of total claims cost, yet it is very hard to detect through manual review alone across a large volume of files.

A RAG-based claims processing and assessment system can shorten processing time from 5–15 days to 1–3 days, with 70–80% of claims auto-classified from the start. In parallel, a fraud-detection system can move from late, manual detection to near real-time monitoring, lifting the fraud-detection rate from roughly 40–60% to above 85% — the savings from reduced fraud alone are often enough to cover the system's investment cost.

The key point is that all health records and customer information are processed entirely within the insurer's own infrastructure, meeting personal-data protection requirements while significantly speeding up the claims process.