Analyse internal data sources (alerts, chargebacks, disputes, anomaly reports, ML models) and external trends (card schemes, partners, law enforcement, industry intelligence) to identify emerging fraud risks related to acquiring business.
Translate observed patterns into well-defined acquiring fraud scenarios, covering areas such as Card-Present and Card-not-present fraud, friendly fraud and dispute abuse, merchant fraud, transaction laundering, enumeration and testing attacks.
Maintain and continuously enrich the Acquiring Fraud Typology Library, aligned with scheme rules, regulatory expectations, and Finom’s risk appetite.
Work closely with the Fraud Risk Manager, product, engineering, and ML teams to ensure correct translation of acquiring fraud scenarios into rules, thresholds and controls as well as machine-learning features and signals.
Participate in back-testing, validation, and tuning of acquiring fraud controls prior to production release.