Method independence
FinGovBench evaluates governance of a financial AI workflow. It does not require any particular model architecture or graph-based submission.
Independent benchmark object
Each public case declares the operational workflow boundary, versioned components,
dependencies, evidence available at the case's as_of time, assurance claims, authority
tier, permitted actions and observed change. This is a system specification analogous to
an architecture or lineage record. It contains no method-specific probabilities, path
contributions or certificates.
Gold outcomes are defined by the financial event and governance contract:
- SEC cases use an official accession-level reported-value pair and a declared workflow contract; their labels remain provisional until independent domain adjudication.
- controlled cases use a prespecified event, authority boundary and executable contract.
- the evaluator, not a submitted method, determines whether the selected action and revalidation scope permit release.
What a submission must do
A method receives the same workflow declaration and must return the affected components, governance action, revalidation components and release decision. A submission may use rules, a flat uncertainty model, an LLM, a knowledge graph or another method. It may transform the neutral workflow declaration into its preferred internal format.
Optional graph-based methods
Graph-based uncertainty propagation is one optional evaluated approach. It must read exactly the same public closed-loop inputs as lexical and flat-uncertainty comparators. No method-specific telemetry or labels are provided.
Anti-circularity requirements
Before version 1.0:
- independent reviewers must adjudicate event validity, required action and revalidation scope without seeing any method prediction;
- submitted predictions cannot alter gold labels or case inclusion;
- all methods receive the same public inputs and sealed test labels;
- genuine and controlled results remain separate; and
- any threshold or learned policy freezes on development data before test evaluation.