F1023 Hybrid NLP and ML Pipeline
Description
The model attempts to predict non-compliance among tax-exempt entities by leveraging embedding-based feature extraction feeding a downstream classifier.
Detailed example
This solution will address multiple F1023 strategies in TEGE and the output will be tailored to improve operational efficiency for each strategy.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
F1023 and F990 contain natural text fields around activity descriptions, mission or purpose statements making it difficult for Tax Exempt Government Entities (TEGE) to detect non-compliance among the population of Exempt Organizations (EOs). This use case provides improved ability to predict non-compliance.
Audit / financial statement impact
The output is not presumed to be high-impact and is not used as the principal basis for significant decisions/actions
Controls / human review
ATO: Not reported; PIA: Not published