From Siloed to Shared: The Consortium Approach to Battling Check Fraud
- Check fraud is growing and becoming more sophisticated
- Consortiums provide faster, more comprehensive risk analysis.
- A layered approach combines consortium data with advanced fraud prevention tools
In today’s banking environment, the threat of check fraud is growing rapidly, fueled by a deluge of data and ever-evolving criminal schemes. Financial institutions (FIs) face mounting pressure as legacy payment systems and digital channels are exploited by fraudsters, while stricter oversight and shrinking access to government data make combating deposit fraud even more challenging. As highlighted in a recent PYMTS blog post, traditional security alone isn’t enough—collaboration and smarter use of collective intelligence are essential.
A pivotal development in fighting check and deposit fraud is the rise of industry consortiums. Rather than working in silos, FIs are turning to these consortiums as “competitive-neutral” spaces for sharing fraud intelligence. By pooling anonymized data and real-time risk signals across multiple institutions, consortium models offer a more holistic view of fraud trends and enable rapid, collective responses to threats. These collaborations, as noted in the PYMTS blog, make individual risk detection more accurate than it would be with internal data alone, while privacy remains protected through advanced encryption and federated data techniques.
Don't Be Afraid of Consortium Data
Why is consortium data important, particularly in check deposit fraud? Well, as noted in the article, "No single dataset, institution or tool can address fraud and risk in isolation."
Consortium data is a powerful component for deposit fraud detection. By leveraging fraud data from multiple financial institutions or internal data sources, consortiums provide real-time insights into fraud patterns, including stolen checks, altered items, and fraudulent accounts. This shared intelligence allows banks to identify risky deposits faster and more accurately than relying solely on transactional specific data.
While there are concerns regarding the use of consumer data, Jeremiah Lotz, senior vice president of enterprise data and experience design at Velera, notes:
"Consumers already expect their financial providers to use their data for safety and experience, so when it comes to transforming that expectation into coordinated defense, the opportunity is significant."
By taking part in consortiums, FIs can use real-time and historical data to analyze transactions and recognize fraud patterns, protecting themselves and their customers.
Consortium Data is Only ONE Component of Deposit Fraud Detection
We caution FIs: Do not rely solely on consortium data as the catch-all for deposit fraud -- there is no single solution that can detect a majority of check fraud.
Consortium data is, in fact, one of seven layers of check fraud prevention tools recommended by OrboGraph:
- Layer 1: Infrastructure, Profiles, & Thresholds
- Layer 2: Outlier - Focused Transactional Analysis
- Layer 3: Behavioral Analysis / Account Status
- Layer 4: Image Forensics
- Layer 5: Check And Account Consortium Data
- Layer 6: Rules Engine, Rules Creation, Continuous Improvement
- Layer 7: Fraud Review/Queues Companions & History
A full description of each layer can be found on our Anywhere Deposit Fraud page.
Each layer is designed with dedicated analyzers, enabling precise yet flexible scoring for complex fraud use cases. By combining these layers, FIs are able to generate highly accurate composite risk scores for each deposited check -- ensuring a high detection level for counterfeits, forgeries, and alterations. This multi-layered technology approach ensures that, even if an item evades detection on one layer, subsequent layers enhance the likelihood of identification and ensure robust and reliable outcomes.