Case Study: Arvato Financial Solutions achieves 90% reduction in false positives and streamlined fraud investigations with Fraud.net

Arvato Integrates Machine Learning to Optimize Fraud Investigations

Arvato Financial Solutions, a Germany-based $5.2B global technology and business services company and operator of AfterPay across nine EU countries, needed to reduce time spent on low-risk transaction reviews, cut false positives, and build AI models that account for country- and client-specific transaction nuances. To address these challenges, Arvato engaged Fraud.net to enhance its fraud detection beyond rule-based checks using machine learning and risk-scoring capabilities.

Fraud.net refined Arvato’s rule logic, trained ML models to score every transaction, and created risk-score bins to automatically approve very low-risk transactions while flagging very high-risk cases (fraud rates >50%) for prioritized review. The Fraud.net solution eliminated many non-high-risk investigations, improved investigator productivity and efficiency, and delivered a 90% reduction in false positives.

Arvato Financial Solutions