SEC · SEC-37 · record R0030

Large Language Model analysis for the Tips, Complaints and Referrals (TCR) system

Securities and Exchange Commission · Division of Enforcement (ENF)

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Service Delivery
Operational functions: Summarization, Risk scoring and triage Derived by keyword rules; see methodology

Problem the AI is intended to solve

The SEC receives high volumes of Tips, Complaints, and Referrals (TCRs) and has limited staff to triage these TCRs effectively. Some TCRs contain large narratives for allegations; AI tools can help summarize submitted information and intelligence for more efficient review by triage staff.

Expected benefits

Large Language Model analysis will be leveraged to more efficiently review submissions to the SEC's Tips, Complaints and Referrals system.

System outputs

Output will include various classification, analysis, trending and other analysis of Tips, Complaints and Referral system data.

Technology

AI classification: Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
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: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
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