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1、 July 2025 Collaborative Data Exchange:The Next Frontier in Fraud Prevention David Barnhardt and Trace Foshee July 2025 Collaborative Data Exchange:The Next Frontier in Fraud Prevention David Barnhardt and Trace Foshee 2025 Datos Insights or its affiliates.All rights reserved.1 Table of Contents Sum

2、mary and Key Findings.3 Introduction.5 Methodology.5 Data Sharing:Current Perspectives on Value.6 Information-Sharing vs.Regulatory Constraints.7 Driving Fraud Benefits.9 Emerging Technologies and Data Type Priorities.13 Implementing Successful Data Sharing.18 Requirements and Success Factors.18 Con

3、tribution Models vs.Passive Consumption.21 Payment Rail Priorities and Real-Time Requirements.23 Regulatory Barriers and Compliance Concerns.27 Technology Implementation and Integration Challenges.28 Vendor Expectations and Service Requirements.31 Regional and Institutional Variations.33 Internation

4、al Data Sharing:Lessons Learned.36 Australia.36 The U.K.and Europe.37 Future Outlook of Data Sharing and Industry Evolution.38 Conclusion.40 A Call to Action.40 List of Figures Figure 1:Perceived Value of Information Sharing for Fraud Detection.6 Figure 2:FCRA vs.GLBA Product Effectiveness Ratings.8

5、 Collaborative Data Exchange:The Next Frontier in Fraud Prevention 2025 Datos Insights or its affiliates.All rights reserved.2 Figure 3:Fraud Types Expected to Benefit Most from Information Sharing.10 Figure 4:Value Assessment of Different Data Types for Fraud Detection.14 Figure 5:AI Fraud Defense

6、Foundation.18 Figure 6:Institutional Requirements for Data-Sharing Participation.19 Figure 7:Satisfaction With Contribution-Required Solutions.22 Figure 8:Satisfaction With Noncontribution Solutions.23 Figure 9:Send-Side Fraud Detection Priority by Payment Rail.24 Figure 10:Receive-Side Fraud Detect