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Fraud Risk Assessment

Analyze claim data and get instant fraud probability scores

KEY High-impact fraud signal · Hints explain why each field matters to the model
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Claimant Profile

Younger claimants with no prior history are flagged more often.
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Demographic feature used alongside other signals.
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Lifestyle context alongside claim history.
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Age band when policy was taken out.
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Incident Details

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Policy Holder at fault + no police report = highest-risk.
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Rural incidents with no witnesses are harder to verify.
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High-value makes with fresh policies are statistically riskier.
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Sport vehicles with new-vehicle age are flagged more often.
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Very high vehicle value relative to deductible is suspicious.
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Brand-new vehicle + same-day accident = very strong fraud signal.
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Very low deductibles on high-value vehicles are suspicious.
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All Perils coverage with a new vehicle raises a red flag.
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Broad coverage on high-value vehicles is flagged more.
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Legal & Fraud Signals

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No police report is one of the strongest fraud indicators.
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No witnesses + no police report = highest fraud probability.
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Accident on same day as policy start is the #1 red flag.
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Very quick claim filing after policy start is suspicious.
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Repeat claimants are significantly more likely to commit fraud.
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Many supplemental claims on one accident are suspicious.
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Recent address changes before a claim can indicate intent to defraud.
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External agents have been statistically associated with more fraud cases.
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Single vehicle incidents with a new vehicle are more suspicious.
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Month the accident occurred.
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Week number when the incident occurred.
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Day of week when the incident occurred.
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Month the claim was filed.
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Week number when the claim was filed.
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Day of week when the claim was filed.
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Driver risk rating assigned by the insurer.
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Insurance representative handling the claim.
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Year the incident was recorded.

info Demo mode: some policy metadata fields (vehicle make, year, policy type) use default values not shown in this form.

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Vehicle Damage Analysis

Upload claim photos for AI damage detection and estimation