Even as carriers are talking about being data-driven, and pouring millions into predictive models and automation, fraud still costs the U.S. insurance industry more than $300 billion a year.
Underneath all that innovation, there’s something the algorithms and reports tend to miss. Intelligent models work off claim forms, billing histories, and transaction patterns. But a lot of fraud cues aren’t numeric but verbal. They appear in how people describe what happened.
Every claim begins with a conversation. And when those statements stay trapped in audio, the system only sees half the picture. That gap is where fraud hides.
The Strongest Fraud Signals Are in the Recorded Statements
If you ask any experienced adjuster where their gut comes from, they’ll tell you it’s the voice. A pause before a date. The way someone repeats a line word for word, like they’ve rehearsed it. Or how a witness suddenly remembers a new detail once they’re told the other part was at fault.
Those signals live in the recorded statement. Yet they’re the one place most fraud systems never look. Carriers already have the data—they just can’t search it, analyze it, or connect it to the rest of the file.
One Missed Contradiction Can Cost Thousands (and It Happens Every Day)
An auto claimant sounded calm, credible, even cooperative.
His summary note read: “No discrepancies found.”
Months later, the same claimant appears in another claim, using the same description, same phrasing, same “consistent” story. But if anyone had looked at the original recording, they’d have noticed he contradicted himself three times about where the impact happened.
No one noticed, because that audio was archived, the summary became “fact,” and the claim paid out.
That’s how it happens every day. Recorded statements are treated like an archive. Something to keep for compliance, not for intelligence. The problem is, that archive holds the richest evidence in the claims process. It’s what IBM calls dark data: information that exists, but stays invisible to the systems that rely on it.
When statements aren’t searchable, adjusters can’t revisit the story, managers can’t compare interviews, and data teams can’t surface recurring patterns. According to Deloitte, the next leap in fraud prevention depends on how insurers handle unstructured data, especially voice and text.
When Statements Become Data, Fraud Patterns Come Into View
Once recorded statements are structured and connected to the rest of the claims' data, conversations start becoming evidence:
- Patterns surface. You start seeing identical phrases across unrelated claims—an early tell for coached narratives.
- Contradictions stand out. Adjusters can compare multiple statements and spot where a timeline or description gently shifts.
- Behavior tells its own story. Long pauses, over-explaining, abrupt corrections become signals of coached or fraudulent intent that you could never analyze before.
- Cross-claim threads appear. Suddenly, the same names or descriptions show up across files, connecting what once looked like isolated incidents.
All these translate into fewer reopens, faster fraud detection, and stronger defensibility when a case heads to arbitration.
Reduce Leakage and Strengthen Fraud Detection with n2uitive Statement Intelligence™
Fraud prevention starts with better visibility.
n2uitive’s Statement Intelligence™ turns recorded statements into structured, searchable data that gives carriers access to the information their fraud systems have been missing. Within minutes of the recording, adjusters get clean, reviewable summaries and transcripts synced to the original audio. Managers and data teams can finally search, compare, and analyze those conversations at scale.
It’s how top insurers are spotting patterns sooner, and giving their models the full picture.
Like a top P&C insurer in North America said:
“n2uitive ensures that we maximize the value of our current technology investments and can easily integrate with our Claims Management System (Guidewire).”
Book a demo to see how Statement Intelligence™ can help your team detect hidden fraud faster.
