by Andrew Jolley, CAMS, Enterprise Fraud Solutions Strategist, FiVerity
This blog is the second in our Collaboration in Action series exploring how AI-enhanced information sharing and collaboration are revolutionizing fraud prevention.
In the modern environment of financial crimes, collaboration among institutions has become a critical weapon in our collective arsenal. Section 314(b) of the USA PATRIOT Act provides a unique framework that enables financial institutions to share information about suspicious activities. Yet, despite its potential, this powerful tool remains underutilized. This post explores the benefits of 314(b), its current challenges, and how emerging technologies can revolutionize information sharing to combat fraud more effectively.
What is Section 314(b) and Why Does It Matter?
Section 314(b) enables financial institutions to share information about suspicious activities under the USA PATRIOT Act. Unlike typical information sharing that might be limited to general insights, 314(b) creates a safe haven for institutions to collaborate on identity sharing, including personally identifiable information (PII), physical evidence, documents, and even drivers' licenses.
The significance of this provision cannot be overstated. Without 314(b), there would be no legal way for fraud investigators to share information nationally about specific identities without violating privacy laws. This gap in information sharing is precisely what fraudsters exploit, allowing them to move from one institution to another, perpetrating similar schemes across multiple banks.
Current Challenges with 314(b) Implementation
Section 314(b) is one of the most powerful tools in our industry’s arsenal to combat fraud and money laundering, especially in complex typologies like elder financial exploitation. Yet despite its promise, actual usage remains frustratingly low.
Why?
The reality is that many financial institutions face operational, technological, and regulatory friction when attempting to use 314(b) effectively. While the concept is solid, the current framework was built for a different era, and it shows when considering that the participation is low.
- Low participation in 314b – FinCEN shows that only 4500 banks and credit unions are signed up to use 314b. This is about half of all depository institutions in the USA. That means only half of the picture is able to be seen.
- Manual Processes – The current 314(b) workflow is manual and slow. Requests are typically sent via email blasts time-consuming, unstructured, and reliant on manual processes of the respondent. It’s a one-sided, reactive approach that doesn’t scale with the speed or complexity of modern fraud.
- Reactive instead of proactive - Reactive 314(b) waits for the fraud to happen, the loss to be reported, and the SAR to be filed. At that point, the damage is often already done. Proactive 314(b) creates a real-time intelligence network where institutions can connect the dots early, detect patterns faster, and stop fraud before it spreads. Taking a more proactive approach will save time and hard-earned deposits for your institutions, keeping your members/customers safe.
- Fighting in the dark – By modernizing the fight against a sophisticated enemy using technology, Financial Institutions can improve upon already existing procedures to combat an emerging threat in a proactive manner.
The potential of Section 314(b) remains largely untapped - not due to limitations in the legislation itself, but rather because of how narrowly we've chosen to implement it. The breadth of SUAs (specific unlawful activities) gives us far more room to collaborate than we’re currently using. By recognizing that, and modernizing how we share, we go from a fragmented defense to a united force.
FiVerity is the natural next step in that evolution: removing the ambiguity, automating the workflow, and creating a real-time fraud intelligence network that works with the regulation, not around it.
How Technology Can Transform 314(b) Collaboration
Automation through leveraging Artificial Intelligence presents exciting opportunities to overcome the current limitations of 314(b):
- Consolidated Information and Pre-Seeded Insights: Automating the 314b process can assist by consolidating information and pre-seeded insights about suspicious activities. When a joint investigation request is initiated, an automated system can pre-fill information about an individual, including risk profiles and patterns of fraudulent activity.
- Identifying Overlapping Investigations: Collaboration using 314b can identify when multiple institutions are investigating the same identity elements, improving the degree of response from investigators by highlighting potential connections.
- Automated Responses: For smaller institutions that lack the time or resources, automation can generate pre-filled responses based on available information, which human investigators can then review and send.
- Predictive Analysis: By analyzing patterns across institutions, artificial intelligence could predict fraudulent activity before it occurs, such as identifying typical muling patterns where accounts are opened in distant geographic locations.
AI has the potential to fundamentally transform how we leverage Section 314(b) by moving us beyond slow, manual processes toward automated, intelligent collaboration.
Automated & Enhanced 314(b) Requests:
Automation can increase the operational efficiency of financial institutions by pre-populating information, enhancing information requests, reducing the burden on investigators, and encouraging broader participation across the industry. Instead of manually crafting each inquiry, institutions could automatically generate risk-relevant data tied to a subject accelerating outreach and improving the quality of shared intelligence. This reduces manual effort, minimizes response latency, and enhances scalability.
Pre-Seeded Risk Profiles & Fraud Signals:
Automation can consolidate internal data and pre-seed 314(b) requests with contextual risk insights such as behavioral red flags, linked identity elements, and cross-channel fraud patterns empowering more targeted and effective collaboration.
Detecting Overlapping Investigations:
What are the benefits of automating your 314b processes? When multiple institutions are investigating similar identity traits. By surfacing these overlaps, Automation can foster faster, more meaningful cooperation between parties who may otherwise never connect.
Smart Response Assistance for Resource-Limited Institutions:
Automation can generate draft responses to inbound 314(b) requests based on existing case files, transactional patterns, or past alerts allowing smaller institutions to participate meaningfully without overextending their resources.
Predictive Collaboration:
By analyzing identity-linked behaviors across the ecosystem, automation could even anticipate fraud patterns before they escalate. Such as identifying money muling schemes, synthetic identity networks, or coordinated social engineering campaigns.
It's time to move from static spreadsheets and slow back-and-forth emails to intelligent, real-time collaboration. Automation by using Artificial Intelligence isn’t just an add-on it’s the key to unlocking the full potential of 314(b).
Real-World Impact: When 314(b) Can Make a Difference
To illustrate the importance of 314(b), consider these real-world examples:
Case Study 1: The $65,000 Wire Transfer
A Michigan credit union member opened a Louisiana credit union account and did nothing with it for 30 days. Then suddenly, a $65,000 wire transfer was initiated from Michigan. The receiving institution suspected fraud—potentially a muling attempt to move money through multiple accounts. Despite reaching out to other 314(b) participants, no one responded initially. After a week, the money was finally returned, but with true collaboration, this type of muling activity could have been predicted and prevented much faster.
Case Study 2: The Multi-Million Dollar Line of Credit
In 2022, a commercial client experienced an account takeover involving an untouched multi-million-dollar line of credit. When several unauthorized large draws totaling over $400,000 were attempted, the fraud was only discovered through an inquiry by the client's spouse. One bank that received funds wasn't 314(b) compliant and initially refused to share information. After this incident, that bank signed up for 314(b), which ultimately helped recover all the stolen funds.
Moving Forward: Transforming Financial Fraud Investigation
The future of 314(b) collaboration lies in moving beyond rules-based approaches toward more sophisticated AI-driven systems. Unlike platforms that take a simple rules-based approach, newer solutions offer the potential for true collaboration and predictive analysis.
Fraudsters are strategic and they know which institutions are proactive or reactive. They deliberately target non-participating institutions and orchestrate complex schemes involving multiple accounts across different geographic areas.
For financial institutions serious about combating fraud, embracing 314(b) collaboration enhanced by AI isn't just an option—it's becoming a necessity. As these technologies mature and adoption increases, we can create a more connected ecosystem that makes it increasingly difficult for fraudsters to exploit gaps in our collective defense.
By transforming how we share information under 314(b), we can not only recover more funds but ultimately prevent fraud before it occurs, protecting both institutions and their customers from financial loss and reputational damage.