What is an AI claims audit?
A claims audit checks whether claims were handled correctly: coverage analyzed properly, liability assessed on the facts, reserves set and updated, deadlines met, and recovery pursued. In an AI claims audit, software reads the whole file, including adjuster notes, correspondence, documents, and payments, and produces findings against a set of handling standards. Human auditors review those findings and decide what to act on.
The audit's purpose stays the same, and so do its criteria, which come from best practices and the carrier's guidelines. AI changes how many files a team can afford to review and how soon.
How is it different from a traditional audit?
A traditional audit samples about 2% of files and reviews them by hand. AI makes it practical to review every file, so the conclusions describe the whole book. Nobody has to extrapolate from a sample.
Manual audits usually look at closed files. AI review also runs on open claims, so an adjuster can fix a missed deadline or a stale reserve while the claim is active.
Every file is scored against the same criteria. That makes adjusters, offices, lines, and TPAs comparable, including their recurring sources of claims leakage.
What do good audit findings look like?
Specific and traceable. Each finding should say what was missed or done well, explain the reasoning, and cite its source in the claim file: a note, a document, a payment. A finding without evidence is hard for an auditor to verify and harder to raise with an adjuster or vendor.
Audit teams usually validate AI findings before relying on them at scale. They check every finding at first, then move to a sample once the results match their own reviews.
What do regulators expect?
The NAIC's Model Bulletin on the Use of Artificial Intelligence Systems by Insurers, adopted in December 2023, asks insurers to maintain a written program for AI governance and controls, including AI used in claims. An AI claims audit fits that expectation best when the roles are clear: the software reviews and explains, and people decide. The Field Guide covers how P&C rules and adjuster licensing apply to AI.
Who uses AI claims audits?
Carrier claims and audit teams use them for internal quality review. MGAs use them to show capacity providers how delegated claims are handled. Carriers and self-insured organizations use them for TPA audits, and reinsurers use the results to see how ceded claims are managed.
Ely Audit is Elysian's AI claims audit software. It reviews open and closed files and cites a source in the claim file for every finding.
