Case Study: Leading Australian Financial Institution boosts fraud detection 400% and cuts manual review 60% with Fraud.net

Leading Bank in Australia streamlines and modernizes fraud prevention with Fraud.net

Leading Australian Financial Institution, one of the largest and longest-established building societies in New South Wales with over 100,000 members and several billion dollars in assets, was relying on a largely manual, simplistic rules-based fraud system that required multiple teams working overnight to review transactions. The bank needed a cloud-based fraud detection and prevention platform to protect card and online purchases, automatically block risky transactions and detect sophisticated fraud earlier in the transaction lifecycle. Fraud.net was selected to address these needs.

Fraud.net implemented a comprehensive risk-analysis and prevention platform featuring an intuitive, flexible rules engine, machine learning scoring, and access to its Collective Intelligence Network of anonymized transaction data. Within 90 days the bank saw a 400% increase in identified fraudulent transactions, a 30% reduction in queued/flagged transactions, and a 60% reduction in manual review person-hours—eliminating the overnight fraud team and delivering substantial operational cost savings. Fraud.net’s solution also enabled earlier detection of fraudsters, limiting financial losses and improving monitoring efficiency.