FSI Case Study4

The fraud propensity scoring model surfaced $1.2M in suspicious claims within the first 90 days of operation — not all of which were ultimately confirmed fraud, but all of which were reviewed before settlement rather than after. The SIU team went from reacting to adjuster referrals to working from a prioritized analytical queue. Their investigation capacity didn't change. Their impact did. On the repairer side, the performance scorecard identified three shops with anomalous supplement rates and estimate inflation patterns. Two were placed on a probationary preferred status pending audit. One was removed from the preferred network entirely. Supplement requests from those three shops had been running at 2.3x the network average for 18 months — invisible in any individual claims review, obvious in aggregate. The fast-track settlement path for low-score claims had a secondary effect nobody had anticipated: average time-to-settlement for clean claims dropped from 19 days to 11 days, because those claims were no longer sitting in the same queue as complex investigations. The insurer's customer satisfaction scores for claims handling improved in the following quarterly survey — one of the few times in the insurer's history that a fraud prevention project also improved the customer experience for honest claimants. What Comes Next DataVines is building a forward-looking repairer risk model — using historical estimate accuracy, supplement frequency, and fraud association patterns to generate a dynamic risk rating for each shop in the preferred network. The goal is to shift repairer oversight from periodic manual audits to continuous data-driven monitoring, with contract renewal recommendations generated automatically at each review cycle. CASE STUDY 04 · FINANCIAL SERVICES & INSURANCE · DATA ENGINEERING & PIPELINES The Reporting Was a Full-Time Job. It Shouldn't Have Been. A fast-growing insurtech firm in Texas was spending five hours every morning pulling data from six different platforms — manually. DataVines automated the entire thing in ten weeks, and the ops team hasn't touched an export file since.

INDUSTRY

InsurTech —Commercial Lines

GEOGRAPHY

United States(Texas-based,n ationwide)

ENGAGEMENT

16 Weeks