NCCBR Data Validation Pilot
Description
AI modules applied to our collection pipelines to flag ingestion errors and assess data quality before analyst review
Detailed example
Flags indicating potential data ingestion errors and data quality assessments for analyst review
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
Improves data quality and reduces manual effort in identifying data ingestion errors enabling analysts to focus on higher-value tasks
Audit / financial statement impact
Data quality validation tool that flags errors for human review no automated decisions affecting public services or individual rights
Controls / human review
ATO: Yes; PIA: Not published
Data needed
NCCBR collection pipeline data financial data ingested from various sources