Identity fraud, from new-account fraud to account takeovers, continues to present major challenges for financial institutions. FIs must have fraud detection and prevention built into every facet of the account lifecycle. But cybercriminals have become increasingly astute at finding new ways to exploit technology and infiltrate consumer accounts. It’s time to rely on more accurate methods of detecting cybercriminal activity.
Technology such as artificial intelligence and machine learning delivers clues about the person on the other end of a transaction or banking interaction with much more accuracy than thin fraud detection that relies on knowledge-based authentication or static passwords. Layering multiple fraud detection and prevention technologies and processes is the key to producing accurate results within an organization’s authentication and fraud-detection platforms.
Key questions discussed in this report:
- Where are financial institutions failing in terms of detecting identity fraud?
- How can technology responsibly use consumer data in making more accurate decisions?
- How can contextual clues be used across the enterprise to more reliably detect impostors and fraud?
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