Fraud is becoming more sophisticated, while traditional rules and fragmented systems are struggling to keep pace. AI can improve detection by identifying anomalies earlier, reducing false positives and uncovering connections between accounts, devices and people involved in fraud. But its success depends on three foundations: high-quality data, explainable models and effective information sharing & collaboration between institutions.
Corporate fraud is usually blamed on the individuals involved. But there is another question worth asking: which management decisions allowed the misconduct to begin, spread and remain undetected? Drawing on two anonymised cases, Elina Moshkovich shows how conflicts of interest, poorly designed KPIs and weak control functions can turn isolated abuse into a systemic business risk.
