Atypical journeys: potential fraud detection

Business question
Do some journeys show atypical patterns suggesting a fraud risk?
What's at stake
For an insurer handling 20,000 homeowners claims a year: 40 to 80 more fraudulent claims caught before settlement, or $320k to $640k in improper payouts avoided.
Data required
Case history (claims or reimbursements) with event sequences and amounts.
Sample result
List of cases showing statistically atypical patterns, for human review.
Demo · 1 min
Illustrative scenario

Consider an insurer handling 20,000 homeowners claims a year. The analysis flags atypical patterns (claims close together, amounts near the coverage limit, inconsistent documents) and routes them to the special investigations unit before settlement.

MetricBeforeAfter
Fraudulent claims caught before settlement, per year100160
Share of fraudulent claims paid out75%60%
Fraudulent payouts per year$2.4M$1.9M
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