Deploying AI-Driven Fraud Detection and Risk Models, Delivering £15M in Annual Savings
The Situation
Across global payment channels, fraud and anomaly cases were rising in volume and complexity. Existing controls were rule-based, reactive, and created false positives that slowed customer transactions and increased manual investigation workload. Fraud losses and operational cost were a Board-level concern, and regulators demanded improved controls, auditability and faster intervention.
The Task
Create and deploy real-time, AI-driven fraud detection and anomaly models, capable of identifying risk patterns at scale, reducing losses, and accelerating investigation. The solution had to integrate into mission-critical payment flows, meet strict regulatory standards, and operate 24×7 without impacting customer experience.
The Action / Approach
- 
Formed a cross-functional delivery team across data science, engineering, product, cyber and compliance; secured executive alignment on funding, deployment and risk governance. 
- 
Designed a cloud-based model pipeline with real-time scoring, event streaming, rollback capability, and full audit trails for regulatory assurance. 
- 
Delivered training datasets using historical signals, behavioural patterns, device telemetry and transactional anomalies; partnered with Operations to validate human-investigated outcomes. 
- 
Implemented dynamic thresholds to minimise false positives and avoid customer disruption, while surfacing high-confidence alerts directly into fraud operations tooling. 
- 
Built continuous model monitoring for drift, accuracy, precision and recall, with automated retraining triggers and safe production rollouts. 
- 
Ran controlled A/B production experiments before full rollout, ensuring no service degradation or latency impact to real-time payments. 
The Result
- 
Reduced fraud-related chargebacks by 20%, delivering £15M+ annual savings across global markets. 
- 
Improved risk detection accuracy, cutting false positives and significantly reducing investigation time for operations teams. 
- 
Enabled real-time blocking of suspicious flows, preventing losses before they occurred rather than after. 
- 
Provided full regulatory auditability of decisions, thresholds, and model lineage — strengthening compliance posture. 
- 
Achieved zero customer-impacting latency increases, maintaining real-time payment performance at scale. 
 
 
                  