Fraud Detection & Anomaly Analytics
Detect fraudulent transactions and suspicious patterns in real time. We build ML-based fraud detection platforms that score transactions, identify anomalies, and reduce false positives for financial services and iGaming operators.
Intelligent Fraud Prevention, Not Just Detection
Rule-based fraud detection systems generate high volumes of false positives while missing sophisticated fraud patterns that evolve faster than static rules can adapt. For financial services firms and iGaming operators in Malta, this means compliance teams overwhelmed by alerts, genuine fraud slipping through, and customer friction from legitimate transactions being blocked.
skios builds ML-based fraud detection platforms that learn from your transaction data to distinguish genuine fraud from legitimate activity with far greater accuracy than rules alone. Our solutions combine supervised models trained on historical fraud cases with unsupervised anomaly detection that identifies novel patterns. Real-time scoring APIs evaluate transactions in milliseconds, and analyst dashboards provide investigation tools with full transaction context for flagged cases.
Fraud Detection Capabilities
Real-Time Transaction Scoring
ML models scoring every transaction in milliseconds with risk assessment, enabling instant approval, flagging, or blocking decisions.
Anomaly Detection
Unsupervised ML identifying unusual patterns across transaction velocity, amounts, geographies, and behavioural indicators.
Analyst Investigation Dashboard
Case management interface with full transaction history, network visualisation, and evidence packaging for compliance review.
Adaptive Learning
Models that continuously retrain on analyst decisions, adapting to new fraud patterns and reducing false positive rates over time.