A substantive expansion and clarification. v2 broadens the scope of the study to include scams, adds the FCC and other agencies to consultations, and introduces new elements for evaluating technology differences and ensuring access to AI/ML tools. It also modifies the pilot program by adding an asset size eligibility requirement and a sunset clause with a follow-up report.
Bank Fraud Technology Advancement Act of 2026
- Sponsor
- Rep. Flood, Mike [R-NE-1]
- Committees
- Financial Services Committee (primary)
- Last action
- Jun 18, 2026
Bottom line
The bill aims to enhance fraud detection capabilities across the financial sector, with a particular focus on supporting smaller institutions through research and potential pilot programs.
What it actually does
This bill mandates that Federal banking agencies conduct a comprehensive study on the use of advanced fraud detection technologies, including artificial intelligence and machine learning, by banks and credit unions. The study must specifically evaluate challenges faced by community financial institutions in adopting these technologies and recommend ways to overcome them. Following the study, the agencies may establish a voluntary pilot program to help smaller financial institutions access these tools.
Proponents argue
Supporters argue that this bill is crucial for modernizing the financial sector's defenses against increasingly sophisticated fraud schemes. They contend that by studying advanced technologies and addressing the unique challenges faced by community financial institutions, the bill will help protect consumers, maintain financial stability, and ensure smaller banks and credit unions can compete effectively in a rapidly evolving technological landscape.
Opponents contend
Critics might argue that mandating a study and authorizing a pilot program without specific funding or a clear implementation timeline could lead to delays and uncertain outcomes. Some may also express concerns about the potential for increased regulatory burden or the privacy implications of expanded data sharing, even for fraud detection purposes, if not carefully managed.
The bill is relatively short and clearly structured, making it accessible for an informed reader to understand its core provisions within a reasonable timeframe.
Section 3
Comprehensive Study on Advanced Fraud Detection Technology
This section requires Federal banking agencies, in consultation with various other federal agencies (including Treasury, FinCEN, FTC, CFPB, and FCC), to conduct a detailed study. The study will examine how banks and credit unions currently use advanced fraud detection technologies like AI and machine learning, their effectiveness, and the barriers to their adoption. It specifically focuses on the challenges faced by smaller community financial institutions.
Supporters argue
Supporters argue that a thorough study is a necessary first step to understand the current landscape of fraud technology, identify gaps, and develop effective strategies to combat financial crime, especially for institutions that may lack resources.
Critics contend
Some critics might suggest that a study could delay action, arguing that the need for advanced fraud detection is already evident and that resources might be better spent on immediate implementation programs rather than further research.
Tradeoffs
The tension lies between the need for comprehensive understanding through a study and the urgency of deploying advanced fraud detection measures. There's also a balance between broad applicability and tailoring solutions for smaller institutions.
Section 3(c)
Report and Recommendations
Within 18 months of the bill's enactment, the Federal banking agencies must submit a public report to Congress detailing their findings from the study. This report must include legislative, regulatory, or supervisory recommendations. These recommendations could involve proposals for shared fraud detection utilities, guidance for AI use in fraud prevention, pilot programs for community financial institutions, and ways to improve public-private information sharing.
Section 4
Community Financial Institution Fraud Technology Pilot Program
This section authorizes, but does not mandate, Federal banking agencies to establish a voluntary pilot program within one year after the study report is submitted. This program would help community financial institutions with less than $10 billion in assets access advanced fraud detection tools. Features could include pooled procurement, shared services, technical support, standardized vendor risk management, and regulatory clarity. The program would sunset after three years, followed by another report to Congress.
The bill defines 'advanced fraud detection technology' broadly to include emerging technologies such as artificial intelligence, machine learning, predictive analytics, behavioral biometrics, network analytics, data fusion tools, distributed ledger-based monitoring tools, and blockchain tracing tools.
Section 2
Why it matters:This is standard legislative practice to establish the scope of terms used throughout the bill.
Case for: Supporters argue that a comprehensive definition ensures the study and subsequent actions cover the full spectrum of relevant cutting-edge technologies, future-proofing the bill's intent.
Case against: No specific opposition is typically raised against a clear and comprehensive definition, though some might argue that such a broad definition could make the study unwieldy or too ambitious.
Estimated impact: This definition sets the expansive scope for the entire study and potential pilot program, influencing the types of technologies and issues that will be examined.
The study requires consultation with a wide array of federal agencies, including the Secretary of the Treasury, the Financial Crimes Enforcement Network (FinCEN), the Federal Trade Commission (FTC), the Bureau of Consumer Financial Protection (CFPB), the Federal Communications Commission (FCC), and other appropriate Federal and State government agencies, including law enforcement agencies.
Section 3(a)
Why it matters:This is standard legislative practice to specify interagency coordination without making it a separate, prominent provision.
Case for: Proponents argue that involving such a diverse group of agencies ensures a holistic and comprehensive understanding of fraud detection, covering financial, consumer protection, communication, and law enforcement perspectives.
Case against: Critics might express concern that involving too many agencies could complicate the study, lead to bureaucratic delays, or create challenges in harmonizing diverse agency priorities and mandates.
Estimated impact: This broad consultation significantly expands the scope and complexity of the study, potentially leading to more robust findings but also requiring substantial coordination efforts.
The establishment of the Community Financial Institution Fraud Technology Pilot Program is explicitly stated as 'may jointly establish,' indicating it is discretionary rather than mandatory.
Section 4(a)
Why it matters:This phrasing provides flexibility to the agencies, allowing them to decide whether to proceed based on the study's findings and resource availability, rather than a deliberate attempt to hide information.
Case for: Supporters of this phrasing argue it provides necessary flexibility, allowing agencies to implement the pilot program only if the study demonstrates its feasibility and value, and if resources are available.
Case against: Critics might argue that making the pilot program discretionary weakens the bill's potential impact, as agencies might choose not to implement it, thereby failing to provide direct support to community financial institutions.
Estimated impact: This discretion means the pilot program's implementation is not guaranteed, potentially limiting the direct, immediate benefits to community financial institutions.