Data provenance connects an output to the source records and processing steps that shaped it. It can include ingestion time, source identity, validation, cleaning, transformations, software versions and the people or systems that handled the data.
Provenance supports reproducibility, investigation and audit. In a financial artificial intelligence system, it helps an investigator reconstruct the evidence available at a past point in time without silently substituting later data or processing logic.
