OMB Individually Reported
Spending Analysis and Budget Execution Risk (SABER) Model
Low riskExact public inventory row
Description
Identify account at risk for over- and under-spend.
Detailed example
Warnings, flags for review and comparison via prediction and classification.
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
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Purpose: Predicts potential budget execution issues by analyzing historical spending patterns across various Treasury accounts and classifications. Benefits: Early identification of spending anomalies allows proactive budget management and reduces the risk of under/overspending.
Controls / human review
ATO: Not reported; PIA: Not published