[Congressional Bills 119th Congress]
[From the U.S. Government Publishing Office]
[H.R. 8671 Introduced in House (IH)]
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119th CONGRESS
2d Session
H. R. 8671
To require the Federal banking agencies to conduct a study on the use
of advanced technologies in fraud detection and prevention, with
particular attention to community financial institutions, and for other
purposes.
_______________________________________________________________________
IN THE HOUSE OF REPRESENTATIVES
May 7, 2026
Mr. Flood introduced the following bill; which was referred to the
Committee on Financial Services
_______________________________________________________________________
A BILL
To require the Federal banking agencies to conduct a study on the use
of advanced technologies in fraud detection and prevention, with
particular attention to community financial institutions, and for other
purposes.
Be it enacted by the Senate and House of Representatives of the
United States of America in Congress assembled,
SECTION 1. SHORT TITLE.
This Act may be cited as the ``Bank Fraud Technology Advancement
Act of 2026''.
SEC. 2. DEFINITIONS.
In this Act:
(1) Advanced fraud detection technology.--The term
``advanced fraud detection technology'' includes artificial
intelligence, machine learning, predictive analytics,
behavioral biometrics, network analytics, data fusion tools,
distributed ledger-based monitoring tools, blockchain tracing
tools, and other emerging technologies used to detect, prevent,
or mitigate financial fraud.
(2) Artificial intelligence.--The term ``artificial
intelligence'' has the meaning given that term in section 5002
of the National Artificial Intelligence Initiative Act of 2020
(15 U.S.C. 9401).
(3) Credit union.--The term ``credit union'' means a State
credit union or Federal credit union, as such terms are
defined, respectively, in section 101 of the Federal Credit
Union Act (12 U.S.C. 1752).
(4) Federal banking agency.--The term ``Federal banking
agency''--
(A) has the meaning given such term in section 3 of
the Federal Deposit Insurance Act (12 U.S.C. 1813); and
(B) means the National Credit Union Administration.
(5) Insured depository institution.--The term ``insured
depository institution'' has the meaning given such term in
section 3 of the Federal Deposit Insurance Act (12 U.S.C.
1813).
(6) Machine learning.--The term ``machine learning'' has
the meaning given that term in section 5002 of the National
Artificial Intelligence Initiative Act of 2020 (15 U.S.C.
9401).
SEC. 3. STUDY ON ADVANCED TECHNOLOGIES IN FRAUD DETECTION AND
PREVENTION.
(a) In General.--The Federal banking agencies, in consultation with
the Secretary of the Treasury, the Financial Crimes Enforcement
Network, the Federal Trade Commission, the Bureau of Consumer Financial
Protection, and appropriate law enforcement agencies, shall jointly
conduct a comprehensive study on the use of advanced fraud detection
technology by insured depository institutions and credit unions.
(b) Required Elements.--The study required under subsection (a)
shall evaluate the following:
(1) Current use and effectiveness.--The current use and
effectiveness of advanced fraud detection technology,
including--
(A) the extent to which insured depository
institutions and credit unions of varying asset sizes
deploy advanced fraud detection technology;
(B) measurable outcomes relating to fraud
reduction, loss mitigation, and consumer protection;
and
(C) barriers to adoption, including cost,
interoperability constraints, regulatory uncertainty,
data access limitations, and liability concerns.
(2) Community financial institution access.--Community
financial institution access to advanced fraud detection
technology, including--
(A) challenges faced by community financial
institutions in accessing or deploying advanced fraud
detection tools;
(B) whether economies of scale disadvantage smaller
community financial institutions relative to large
community financial institutions;
(C) options to facilitate shared services, utility
models, managed-service providers, or consortium-based
fraud detection platforms; and
(D) recommendations to ensure regulatory guidance
is appropriately tailored to avoid discouraging
adoption by smaller community financial institutions.
(3) Artificial intelligence and machine learning.--
Artificial intelligence and machine learning, including--
(A) the use of artificial intelligence and machine
learning models, applications, and tools in detecting
fraud patterns, anomalies, synthetic identity fraud,
and real-time payment fraud;
(B) governance frameworks used by insured
depository institutions and credit unions to manage
fraud model risk, explainability, and validation; and
(C) interactions between fraud detection models and
consumer protection laws.
(4) Information sharing and public-private partnerships.--
Information sharing and public-private partnerships,
including--
(A) the effectiveness of existing information-
sharing frameworks;
(B) whether expanded public-private partnerships or
centralized fraud utilities would enhance detection
capabilities;
(C) the feasibility of a voluntary fraud analytics
consortium accessible to community financial
institutions; and
(D) privacy, data protection, and cybersecurity
considerations associated with expanded data sharing.
(5) Payments system risks.--Payments system risk,
including--
(A) fraud risks associated with electronic funds
transfers and checks; and
(B) whether advanced analytics can reduce fraud
while preserving settlement finality and payment system
stability.
(6) Regulatory and supervisory considerations.--Regulatory
and supervisory considerations, including--
(A) whether existing supervisory expectations
create barriers to innovation;
(B) the need for interagency guidance, regulatory
clarity, or safe harbors to support technology
adoption;
(C) opportunities to harmonize expectations across
Federal banking agencies; and
(D) whether additional training for Federal banking
agencies staff is necessary to promote effective
regulation and supervision of financial institutions'
use of advanced fraud detection technology, especially
for community financial institutions.
(c) Report and Recommendations.--
(1) Report.--Not later than 18 months after the date of
enactment of this Act, the Federal banking agencies shall issue
a report to the Committee on Financial Services of the House of
Representatives and the Committee on Banking, Housing, and
Urban Affairs of the Senate containing all findings and
determinations made in carrying out the study required under
this section, and make such report publicly available, except
for classified or supervisory information.
(2) Recommendations.--The report required under paragraph
(1) shall include legislative, regulatory, or supervisory
recommendations which may include--
(A) proposals to support shared fraud detection
utilities or consortium-based analytics platforms;
(B) guidance or safe harbors to encourage
responsible artificial intelligence use in fraud
prevention;
(C) pilot programs tailored to community financial
institutions; and
(D) recommendations to strengthen public-private
information sharing consistent with privacy and civil
liberties protections.
SEC. 4. COMMUNITY BANK FRAUD TECHNOLOGY PILOT PROGRAM.
(a) In General.--Not later than 1 year after submission of the
study under section 3, the Federal banking agencies may jointly
establish a voluntary pilot program to facilitate community financial
institution access to advanced fraud detection tools.
(b) Program Features.--The pilot program described in subsection
(a) may include--
(1) pooled procurement or shared services models;
(2) model validation assistance or technical support;
(3) standardized vendor risk management templates;
(4) regulatory clarity regarding model governance
expectations; and
(5) collaboration with the Department of the Treasury and
law enforcement to provide anonymized fraud typology data
feeds.
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