OMB Individually Reported

Blockchain Analysis

Medium riskExact public inventory row

Description

By utilizing this AI-powered blockchain analysis platform, investigators can uncover hidden connections across blockchain networks, detect illicit activities, and significantly reduce the time required for manual analysis, enhancing HSI’s ability to combat transnational crime effectively.

Detailed example

The platform’s outputs include confidence scores for address attributions, risk flags based on behavioral typologies, identification of hidden connections across blockchain ecosystems, and plain-language summaries of smart contracts.

AI / analytics pattern

Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.

Automation level / stage

c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.

Expected benefit

The use of AI within TRM Labs improves HSI’s ability to uncover hidden connections across blockchain ecosystems, detect illicit behaviors, and reduce the time required for manual analysis.

Audit / financial statement impact

Despite falling into a presumed category of high-impact AI, this use case does not meet the definition because the AI’s outputs serve primarily as inputs to an investigative process rather than making legally binding or material decisions itself. HSI investigators review, validate, and contextualize the AI-generated outputs before integrating them into any official case management system. Enforcement decisions and outcomes arise from a full investigative process that includes judicial review and other safeguards, thereby distancing the AI outputs from direct impact on civil liberties or privacy

Controls / human review

ATO: No; PIA: Not published

Data needed

The platform uses vendor AI models trained and tested on public blockchain ledger data (public/external), as well as proprietary data, internal attribution and scoring data, behavioral data, network data, and synthetic data.