DOJ · DOJ-0029 · record R1500

Southwest Border Transaction Record Analysis Center (SWBTRAC)

Department of Justice · Department of Justice / ATF

Overview

Development stage: DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation: Presumed high-impact, determined notSource: b) Presumed high-impact, but determined not high impact
Impact justification: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
Start date: 2024-01 (month precision)Source: 01/2024
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Procurement and Financial Management
Operational functions: Risk scoring and triage Derived by keyword rules; see methodology

Problem the AI is intended to solve

The purpose of the AI use case in Southwest Border Transaction Record Analysis Center (SWBTRAC) is to monitor cross-border financial transactions and identify unusual activities more efficiently. By integrating AI-driven anomaly detection, trend analysis, and risk scoring, it simplifies manual review and directs attention to truly irregular transfers. This approach ensures that investigative focus is applied judiciously, improves accuracy, and enhances strategic use of resources in addressing cross-border financial concerns.

Expected benefits

The expected benefit is faster recognition of outlier scenarios, focusing on meaningful transactions rather than all equally.

System outputs

The AI features provide alerts, highlight unusual transfers, and explain why certain activities warrant closer observation.

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): Redacted for cybersecurity purposes.
Custom-developed code: No
Public source code: Not reported

Sourcing

How it was built: Purchased from vendorSource: a) Purchased from a vendor
Vendor (as reported): Western Union
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Yes
Privacy Impact Assessment: Not reported
Authorization to Operate: No
Demographic features: This AI use case utilizes one or more of the demographic variables listed in compliance with all federal laws and agency regulations.
Training and evaluation data: The case owner relied on DOJ AI governance practices to select and prepare data, as well as evaluate performance.
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported