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Paper · arXiv

FinVerBench: Benchmark Validity and Calibration in Large Language Model Financial Statement Verification

We introduce FinVerBench, a benchmark and validity study for financial statement verification: determining whether a set of corporate financial statements is numerically consistent from the information shown to the model. FinVerBench is built from SEC 10-K XBRL filings for 43 S&P 500 companies and defines a four-category error taxonomy covering arithmetic, cross-statement linkage, year-over-year, and magnitude perturbations. We attempt fifteen contemporary LLM evaluations and report fourteen complete runs; a Gemini 2.5 Pro run is excluded from the main comparison because 40/108 gateway calls failed. All binary metrics exclude underdetermined positive instances whose perturbed line item is...

AuthorsSilu Panda
Primary categorycs.AI
Published28 May 2026
Last updated at source28 May 2026
cs.AI
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