VA · VA-25-3480 · record R2087

Smart Pension Automation

Department of Veterans Affairs · VBA: Veterans Benefits Administration

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: High-impactSource: a) High-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: Not reported

Mission

Topic area: Government Benefits Processing
Operational functions: Claims and case processing Derived by keyword rules; see methodology

Problem the AI is intended to solve

Reduce the overall average of days to complete a pension related benefit claim. Currently, there is a batch claim processing system in place with Pension Automation that leverages Camunda and is currently only able to process 300 claims/night due to constraints with the original solution. Due to the constraints, a large number of claims are offboarded each night for manual resolution.

Expected benefits

The AI solution is expected to increase the number of claims awarded on a daily basis by 10% with the minimum viable product (MVP) solution and then continue to improve with iterative deliveries after the MVP solution.

System outputs

The AI solution will output reporting data on which claims were awarded or off ramped on a daily basis. The solution will also provide auditable information on why a decision was made for a human to review.

Technology

AI classification: Agentic AISource: Agentic AI: AI systems that perform tasks or make decisions autonomously with minimal human intervention.
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