QCEW NAICS Autocoder
Description
The primary data source for the Quarterly Census of Employment and Wages (QCEW) is administrative data from state unemployment insurance programs. Some of these records are submitted without a valid North American Industry Classification System (NAICS) code.
Detailed example
The model is a random forest classifier trained on millions of QCEW records. It outputs the NAICS codes with the highest predicted probability given a business name.
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
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
The tool is intended to reduce the burden on human reviewers of these uncoded records by recommending the most likely NAICS codes. It also reduces the burden on the program office by reducing printing and mailing costs of soliciting unclassified data.
Audit / financial statement impact
Used for survey processing for statistical purposes
Controls / human review
ATO: No; PIA: Not published
Data needed
QCEW records (legal name, trade name, and NAICS fields)