VA · VA-25-1930 · record R2075

Claims Processing Automation Quality Auditor POC

Department of Veterans Affairs · OIT: Office of Information & Technology

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

In an automation-driven claims process, this tool will act as an entry point for quality reviews: Perform claims quality audits to identify and request NQA reviews or VCE corrections based on automated claims processing anomalies/errors. Function of the model: Perform claims quality audits to identify and request NQA reviews or VCE corrections based on automated claims processing anomalies

Expected benefits

Increased efficiency, improved benefit outcomes, faster decisions for Veterans.

System outputs

Within that automation workflow, the claim will be offramped (based on the criteria of the claim and resulting automated decision) to a human to be worked.

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): 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