SBA · SBA-7 · record R3168

7(a) Purchases ML Model

Small Business Administration · OCA: Office of Capital Access

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 high impact: This AI system does not meet the criteria of any of the six pillars that make up High Impact AI in Memorandum M-25-21.
Start date: 2026-01-01 (day precision)Source: 01/01/2026 00:00:00
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Service Delivery
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Manual review of all 7(a) loan purchase applications is resource-intensive, but OCA needs to maintain quality control and minimize PIIA error rates.

Expected benefits

Reduced manual review burden while maintaining or improving quality, faster processing times for legitimate applications, and optimized use of limited review staff resources.

System outputs

By leveraging data analysis and machine learning, OCA can focus reviews on the applications that require manual review. This project will enable OCA to reduce the amount of effort expended on manual reviews without increasing PIIA error rates.

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): GPTS, E-Tran, FMS
Custom-developed code: Yes
Public source code: Not publicly available - Government internal use code

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
Vendor (as reported): In-house development
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 publicly available
Authorization to Operate: Yes
Demographic features: Not applicable - System does not involve individual-level decision-making
Training and evaluation data: Internal agency data and historical records relevant to the use case.
Federal Data Catalog: Not applicable - Internal agency data not publicly disclosed

Governance

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

Pre-deployment testingReported in progressSource: b) In-progress

AI impact assessmentReported in progressSource: b) In-progress

Independent reviewReported in progressSource: d) In-progress

Ongoing monitoringReported in progressSource: b) Development of monitoring protocols is in-progress

Operator trainingReported in progressSource: b) Establishment of sufficient and periodic training is in-progress

Fail-safeNot applicableSource: b) Not applicable

Appeal processReported in progressSource: c) Establishment of an appropriate appeal process is in-progress

User and public consultationReported in progressSource: Planning includes direct usability testing during pilot phase, establishment of feedback mechanisms, and consultation with end users and stakeholders throughout development.Flag: free-text answer

Potential impacts and how they were identified

Impact assessment in progress. Will include stakeholder consultation, testing protocols, and establishment of mitigation measures before deployment.