What's the difference between claims audit software and claims QA software?

The terms overlap. Claims QA, or quality review, usually means ongoing checks on open files; a claims audit usually means a periodic review of closed files. Many tools do both, and AI-based tools make it practical to run quality review continuously across the book.

Does claims audit software work with an existing claim system?

Most tools sit alongside the claim system and read files and data from it. Ask each vendor which systems it connects to, how files come in, and whether it can review claims your TPAs handle as well as in-house files.

How should we evaluate an AI claims audit tool?

Run it on files your auditors have already reviewed and compare the findings. Check whether each finding cites a source in the file, whether it handles your most complex lines, and how quickly your team can verify its work. Ask the vendor to show accuracy on your own claims.

Field Guide definitionSeptember 27, 2026

Claims audit software

Claims audit software helps carriers, MGAs, TPAs, and self-insured organizations review claim files for handling quality and compliance. It manages audit criteria, records findings, and reports results; AI-based tools also read the files and draft the findings.

What does claims audit software do?

At minimum, it gives auditors a structured way to select files, score them against criteria, record findings, and report results. Some tools stop at workflow and scoring, and a person still reads every file. Others use AI to read the file and produce findings for auditors to review; see AI claims audit.

Typical audit areas are coverage and liability determinations, reserving accuracy, statutory deadlines, investigation, subrogation, defense counsel and litigation strategy, vendor management, and documentation.

Why do claims teams buy it?

Manual audits are slow. They typically sample about 2% of files, often after the claims have closed. Software makes scoring consistent, lets a team cover more of the book, and rolls individual findings into portfolio trends, such as a leakage pattern in one office, one line, or one TPA.

What should you look for in claims audit software?

Can it review every file in the book, or only the sample a person has time to read?
Can it review open claims, so issues get fixed before they affect the outcome?
Does every finding cite its source in the claim file and explain its reasoning?
Does it read notes, documents, correspondence, payments, and other media, or only structured fields?
Can it apply your own guidelines and authority levels as well as general best practices? Does it need them loaded before it can start?
Can auditors check all findings or a sample, and do they make the final call?
Does it handle your hardest lines, such as litigated liability, bodily injury, or construction defect?
Does it work with the claim systems and data you already use, in-house and at your TPAs?
Does it roll findings into trends that claims leaders and underwriters can act on?
Can you explain how it works and document its controls, as the NAIC's 2023 model bulletin on insurers' use of AI expects?

Who uses claims audit software?

Carrier claims quality and audit teams, MGAs with delegated claims authority, TPAs preparing for client audits, self-insured organizations overseeing an administrator, and reinsurers reviewing ceded claims. The right tool depends on the volume and complexity of the book and on how much of it the team needs to see.

Ely Audit is Elysian's AI claims audit and QA software for open and closed claims, purpose-built for complex claims.

FAQ

What's the difference between claims audit software and claims QA software?
The terms overlap. Claims QA, or quality review, usually means ongoing checks on open files; a claims audit usually means a periodic review of closed files. Many tools do both, and AI-based tools make it practical to run quality review continuously across the book.
Does claims audit software work with an existing claim system?
Most tools sit alongside the claim system and read files and data from it. Ask each vendor which systems it connects to, how files come in, and whether it can review claims your TPAs handle as well as in-house files.
How should we evaluate an AI claims audit tool?
Run it on files your auditors have already reviewed and compare the findings. Check whether each finding cites a source in the file, whether it handles your most complex lines, and how quickly your team can verify its work. Ask the vendor to show accuracy on your own claims.

Related definitions

AI claims audit
An AI claims audit uses AI to review claim files for handling quality, including coverage and liability decisions, reserving, timeliness, and recovery. It can review every file in a book, where a manual audit samples about 2%, and human auditors check its findings.
TPA audit
A TPA audit reviews how a third-party administrator handles claims for a carrier, MGA, or self-insured organization. It checks claim files against the client's guidelines, authority levels, and best practices, and it supplies the evidence for TPA oversight.

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