Fraud, waste and abuse in Nigerian health insurance.
Most leakage is invisible one claim at a time. It only becomes obvious as a pattern — which is exactly why individual review keeps missing it.
Fraud, waste and abuse — usually shortened to FWA — is the quiet tax on every HMO's loss ratio. It is easy to talk about in the abstract and hard to catch in practice, because on any single claim it rarely looks like anything at all. Understanding the difference between the three is the first step to doing something about it.
Fraud, waste, and abuse are not the same thing
Fraud is deliberate deception for gain: billing for a service that was never delivered, or submitting the same claim twice hoping one slips through. Waste is spend that adds no value — unnecessary tests or services, often not malicious, but avoidable. Abuse sits between the two: practices that are not outright fraud but that push cost beyond what is reasonable, such as coding a procedure to a higher-cost category than what was actually done.
On a Nigerian book, the common shapes are familiar: duplicate submissions, upcoding, and claims where the procedure or prescription does not fit the stated diagnosis.
Why individual review misses it
A single duplicate looks like a clerical error. A single upcoded procedure looks like a judgement call. A prescription that is slightly off for a diagnosis looks like clinical discretion. None of these trip an alarm on their own.
FWA is a pattern problem wearing the costume of individual claims.
The signal lives across a provider's history and against the behaviour of peers — how often this provider bills this code, how their mix compares to similar facilities, whether the same member-service pair has appeared before. No human reviewer can hold that much context in their head, and asking them to try just slows the clean claims down without catching the pattern.
Catching it before the money leaves
The fix is to move detection to the point of decision and to do it at portfolio scale. Fraud, waste and abuse detection that runs during adjudication screens every claim for FWA signals as it is processed, flags the ones that match a suspicious pattern, and routes them to an investigations queue with the evidence attached — all while the clean majority of claims keep flowing straight through.
Two things make this work in the Nigerian context specifically. First, detection has to be calibrated to the local disease burden and to local provider and tariff patterns, rather than imported from a market where the baseline behaviour is different. Second, every flag has to be recorded in an append-only event log, so an investigation starts from a trail that cannot be quietly edited.
The point
You cannot stop what you cannot see, and you cannot recover spend that has already left. Treating FWA as a pattern to be caught at the point of decision — rather than a set of individual claims to be judged one at a time — is the difference between a report that tells you what you lost and a control that prevents the loss.
Find the leakage in your own book.
We walk through fraud, waste and abuse detection on the claims patterns your team sees every day.