Why more data signals aren’t solving the fraud problem

Financial institutions have spent the last decade expanding the number of signals available to improve fraud detection. Device intelligence. Behavioral intelligence. Identity data. Transaction patterns. Consortium data. Biometric data. Yet more data has not necessarily delivered better outcomes.

As financial institutions invest in AI and next-generation technologies, the quality, context, and durability of the signals behind those decisions become critical. The future of fraud prevention will not be defined by the volume of data, but the intelligence needed to transform signals into explainable and actionable decisions.

View this timely discussion with industry thought leaders as we explore:

• How agentic AI is reshaping fraud decisions and why explainability becomes critical

• Why adding more fraud signals doesn't automatically improve risk decisions

• How to distinguish valuable, durable signals from those that quickly lose effectiveness

• Why turning data into decisions across digital workflows remains a challenge

• What this means for fraud, digital, and risk leaders