NANO FWA
AI-powered Fraud, Waste and Abuse Management Solution
Catch it before the payment leaves, not after
Recovering a fraudulent payment means persuading someone with no incentive to cooperate to give the money back, months later, usually for a fraction of it. Preventing the same payment costs a review. That gap is the entire business case for payment integrity, and it is why NANO FWA sits before adjudication rather than after it.
The low-code automation platform brings the whole picture of a suspect claim into one view — history, provider pattern, member pattern and the rules it broke — so an investigator opens a case already knowing what they are looking at.
What NANO FWA gives a payer
- Fewer claim errors reaching adjudication
- Lower cost and less manual intervention per claim
- Cost-containment targets that are met rather than reported
- Payment integrity handled as a system, not a recovery exercise
- Fraud, waste and abuse caught before the claim is paid
- Higher auto-adjudication rates, with payment accuracy to match
- Compliance you can evidence, on demand, per claim
- Shorter investigations, because the case arrives assembled
The hard part was never recognising fraud once you are looking at it. It is the volume: finding the few claims worth a human hour inside millions that all look ordinary. That is a machine problem, and it is the one this platform solves first.
The detection models were designed with investigators rather than for them, which is why the output is a case an investigator can work rather than a score they have to interpret. NANO BRAIN — trained on hundreds of millions of processed claims and approvals — flags fraud, waste and abuse as part of the same automatic pass.
Case management efficiency
up by around 58%
in NANO deployments
Regulatory compliance,
evidenced
Return on investment
of up to 25:1
in NANO deployments
Faster investigation, fewer dead ends
A unified view of each FWA case gives payers a single place to triage, investigate and document — with the evidence attached to the case rather than scattered across inboxes.
The same models surface emerging patterns, not just known ones: schemes change faster than rule sets, and a system that only catches what it was told about last year is a system that catches last year.
Industry estimates put losses to fraud, waste and abuse at around 12% of annual healthcare spend. Whatever the true figure in your book, it is large enough that a percentage point of it pays for the programme.
See what a percentage point of your loss ratio is worth
Related products
Products in the suite that work alongside this one.