Insurance Claim Fraud Detection: Why It Starts Long Before the Claim
Ask 100 insurance professionals what insurance fraud is, and 99 will describe claims fraud. Ask when they start thinking about it, and most will say, "When the claim is filed." Makes sense, but only thinking about claims fraud once the claim is filed quietly costing carriers more than they realize.
Claims fraud is typically not a split-second, in-the-moment decision. It's generally premeditated. And the behavioral signals that distinguish a legitimate claimant from someone planning to manipulate a payout exist long before FNOL. They're there at the quote, and they're there when the person logs into the policy admin system in the weeks before filing. They are there when the person is filling out the claims intake form. The fraud doesn't start at the claim; the submitted claim is just where it becomes expensive enough to notice.
Not for us. We think about fraud detection across four stages: Pre-Bind, Policy Admin, FNOL, and Post-Claim. Most carriers only have real visibility when the fraud is already furthest along.
Pre-Bind: The Signal Before the Policy Exists
Have you ever seen the movie Minority Report, where Tom Cruise works for a specialized "pre-crime" police department that predicts and stops crime before it happens? Well, ForMotiv doesn't employ psychics, nor do we enforce the law, but we do have our own type of "pre-fraud" identification that surprises most claims and SIU leaders the first time they hear it.
The behavioral patterns predictive of future claims activity often show up during the quoting process, before the policy binds and long before there's anything to investigate.
While carriers are very focused on understanding purchase intent to drive growth these days, there are limitations if you only look at applicants through the conversion lens.
Think about two applicants: one who just bought a car and needs coverage before driving it off the lot, and one who backed into their garage this morning and knows they'll file a claim within the week. Both answer your underwriting questions identically, neither is obviously misrepresenting anything, both are identified as being "high propensity shoppers" - but these two seemingly identical applicants will have dramatically different LTVs.
The key is understanding
We work with a majority of the top 10 P&C carriers, and the most sophisticated ones use pre-bind behavioral signals as a claims-propensity flag that routes certain policies for closer underwriting scrutiny before they ever bind. Not a reason to deny coverage, but as a signal that the policy warrants closer review upfront and priority review if a claim comes in later.
Policy Admin: Where Bad Actors Set the Stage
This is the part of the lifecycle that gets the least attention, and it's arguably where the most preventable loss happens. Before a fraudulent claim is filed, the bad actor usually has work to do: test the login credentials, redirect the payout by changing the bank account, intercept communications by updating the email or phone number, manipulate the profile, etc. These are just a few examples of how fraudsters "warm up" accounts before committing the crime. All of it happens inside the policy admin system, and it is not normally flagged because these are all normal, everyday situations that legitimate policyholders and claim filers do. In a lot of cases, they're using legitimate PII that also wouldn't be flagged by internal fraud systems.
The key is that the way they do it is behaviorally anomalous to how normal customers behave. The pace and behavior of account takeover is different, the navigation is different, the repeated login is suspect, the networking/device mismatch information is suspect, the robotic or scripted edits to payment and contact fields look nothing like how a real policyholder manages their account.
What makes catching this behavior even tougher is that many bad actors do this setup work and then file the claim off-channel, by phone, paper, or fax, to throw carriers off the scent. By the time the claim comes in through a call center, there's no digital signal left at the claims stage. The only window that existed was inside the policy admin system, and if nobody was watching it, it's gone.
That's why more and more carriers are layering Behavioral Intelligence across the enterprise. If you have
FNOL: Triage at the Moment of Filing
This is where most fraud detection tools already live, and for good reason: real-time detection at FNOL is where the most immediate loss avoidance happens. However, most tools today focus on the actual information submitted, i.e., whether the image or document they uploaded was real or AI-generated, not how it was submitted. That's where ForMotiv comes in. Anomalous behavior on specific fields, unnatural navigation that suggests the person knows exactly what they're looking for, field edits consistent with payout maximization - all of these signals fire before the claim is submitted, and suspicious sessions get routed to SIU with a behavioral record already attached.
A flag at FNOL means more when it's corroborated by risk signals from the original application or policy admin system. The pattern is stronger, the intent is harder to argue against, and SIU has a thread to pull instead of a bare alert. Carriers tell us the referral quality problem is as real as the detection gap itself: high-volume, low-context alert queues waste investigator time on cases that don't hold up. With a continuous feedback loop, our risk alert accuracy continues to improve, reducing the high-volume, low-context alert queues that waste investigator time.
Post-Claim: Giving SIU the Record to Build the Case
Catching fraud in real time is the goal, but it doesn't always happen. Claims pay out, policies get rescinded after the fact, and regulators come calling for lookback records. At that point, the question isn't "How do we flag this faster?" It's "Can we reconstruct what happened?" If the behavioral data was captured from day one, investigators have a complete, searchable record: every session, every screen, every field edited, from the original application through every account interaction in between. That's where having a
Bottom Line
Insurance claims fraud isn't just a claims problem; it's a lifecycle visibility problem. The same bad actor who files a fraudulent claim in month six was probably showing behavioral signals at the original application and may have been active in the policy admin system in the weeks before filing. The fingerprint is continuous, even though the fraud touches multiple systems and teams.
Most carriers are trying to detect it at one stage, usually FNOL, because the teams that own each stage are siloed from each other. The carriers making the most progress connect those stages with a single behavioral layer with ForMotiv that accumulates evidence from the first session and hands investigators a complete record when a case needs to be built.
The fraud signal is rarely missing. More often, it's present but invisible to a system that only started looking when the claim came in.
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