FSI Case Study2

The four Friday reports were retired within three weeks. The state leads who had been building them were redeployed to actual claims review work — looking at patterns and coaching adjusters, not compiling numbers. The claims management team recovered 60 hours a month that had previously gone into manual reporting. The aging heatmap surfaced something the VP had suspected but couldn't confirm: a specific adjuster in the Virginia center had an unusually high concentration of complex auto liability claims that were all stalling between investigation and negotiation. It wasn't a performance issue — it was a workload issue. Twenty-three claims were redistributed. Average cycle time for that complexity tier dropped 18% in the following month. On the reserves side, the actuarial team ran their first reserves review using internal resolution data instead of industry benchmarks within two months of go-live. The reserves recommendation for the auto liability line was adjusted downward by $340K — a direct financial impact from having reliable internal data for the first time. What Comes Next DataVines is now working with the insurer on a predictive claim complexity model — using first notice of loss details, coverage type, and claim history to score complexity at intake and automatically route claims to the right adjuster tier. The goal is to match claim difficulty to adjuster experience before the claim ever lands in a queue, not after it has been sitting there for a week. CASE STUDY 02 · FINANCIAL SERVICES & INSURANCE · EXECUTIVE BI & REPORTING The CFO Was Always the Last to Know When a Policy Line Was Underperforming A mid-sized life and health insurer had nine separate reports landing in the CFO's inbox every month. DataVines replaced all of them with one dashboard that updated itself every morning.

INDUSTRY

Life & HealthInsurance

GEOGRAPHY

United States(Midwest & Southeast)

ENGAGEMENT

10 Weeks