Prescriber intelligence
Fraud has an author. We follow the pattern back to the source.
A single claim can look clean in isolation. Inspector AI links the sequence — same prescriber, same pharmacy, same molecule — because that is where the pattern actually lives.
Most detection stops at the transaction: is this claim valid on its own? But doctor shopping and prescription cloning are relationship patterns, not single-claim patterns — visible only when you connect the prescriber, the pharmacy, and the sequence of claims across time. Inspector AI evaluates all three.
Why claim-level scoring misses the pattern
A shotgun-prescribing pattern, a prescriber's claims spread unnaturally across many pharmacies, or a prescription cloned and resubmitted months later — each individual claim can look completely valid. The tell only appears when you connect claims across a prescriber, a pharmacy, or a subscriber over time. Systems that evaluate transactions one at a time structurally cannot see it.
What prescriber-level detection looks like
Inspector AI evaluates patterns across the prescriber, the dispensing pharmacy, and the subscriber — not just the individual claim. That includes prescribing concentrated in unusual patterns across a prescriber's book, claims for the same subscriber spread unnaturally across many pharmacies, and prescriptions with an identical medication list and prescriber resubmitted after the original episode should have ended. WAFL's Fraud and Abuse categories are built on exactly this kind of sequence analysis, not single-claim rules.
This is the fraud story, not the waste story
Generic substitution and early refills are waste and utilization problems — real money, but not deception. Prescriber- and pharmacy-pattern detection is where behavioral fraud risk actually shows up: coordinated activity that looks reasonable claim-by-claim and only reads as deliberate once you see the sequence. In a WAFL breakdown of a real Latin American book, Behavioral Fraud Risk — doctor shopping, cloned prescriptions reused months later, pharmacy branch dispersion, and incoherent polypharmacy — accounted for 4.6% of pharmaceutical spend. It's the smallest of the five WAFL categories by dollar volume, and the one most systems never see at all, because it only exists at the sequence level.
What this means for your roadmap
It means the three-week proof of concept doesn't just show you which drugs to switch to generic. It shows you which prescribers and pharmacies are generating patterns worth a closer look — with the same rigor as the waste numbers, on your own data, not an industry average.
of pharmaceutical spend was behavioral fraud risk — doctor shopping, cloned prescriptions, and pharmacy dispersion — measured on a real Latin American book, not modeled.
See what patterns show up in your own book
A three-week proof of concept on your real claims data. No integration required.