Case Study: AXCESS Financial achieves nearly 100% reduction in successful scam attempts with CallMiner Eureka interaction analytics

AXCESS Financial Finds & Stops Fraud with Interaction Analytics

Axcess Financial, a consumer financial services firm with about 3,500 employees and 35,000–40,000 daily customer contacts, was losing over $360,000 a year to social-engineering scams that succeeded roughly once a week. Already using CallMiner for QA, Axcess turned to CallMiner’s Eureka interaction analytics to try to move from reactive investigations to proactive fraud detection.

Using CallMiner Eureka and TopicMiner, Axcess built predictive scorecards (0–600) that flag high-risk calls (intervention threshold >80), categorize caller behavior and cross-check metadata, then tuned category weights to scale without excessive false positives. The CallMiner-driven solution exposed fraud rings’ MO, identified targeted stores, and drove a nearly 100% reduction in successful scams (about 99.99% — only one success in six months), eliminating the bulk of the prior annual losses.

Axcess Financial

Allyson Keown

Speech Analytics Analyst