From Silos to Signals: Strengthening Fraud Detection With Integrated Intelligence

Current fraud tactics involve multi-stage attacks that target identities, accounts, transactions, and communication channels. By the time fraud is detected, it’s often too late. While fraudsters collaborate and share intelligence, many financial services providers—which include fintech companies, payment processors, digital wallets, lending platforms, and other technology-driven firms—are still fighting fraud in disconnected silos, across internal teams and between organizations. 

To effectively protect consumers and reduce fraud losses, financial services providers need connected strategies that bring together identity signals, device signals, risk indicators, and ongoing behavioral insights throughout the entire customer lifecycle. That includes layered defenses, dynamic identity verification, real-time risk assessments, the use of machine learning tools, and shared intelligence. With this connected approach, distinguishing bad actors from legitimate customers becomes easier and fraud is stopped more effectively.

Foreword

This report, sponsored by Plaid, explores how siloed fraud prevention leaves gaps that fraudsters frequently exploit. It examines why many financial institutions struggle to detect complex fraud patterns, which often occur across multiple channels or institutions. This report outlines the need for connected and adaptive strategies that include identity, risk, and behavioral signals, along with shared intelligence to better detect identity fraud in real time. 

This report was adapted from the 2025 Identity Fraud Study: Breaking Barriers to Innovation, published by Javelin Strategy & Research in March 2025. Javelin Strategy & Research maintains complete independence in its data collection, findings, and analysis.