mlsanityData to 7 Oct 2026

VERA-8B: Evidence-Grounded Audit Risk Reasoning from SEC Filings

arXiv 2608.28402 ↗First posted 28 Aug 2026cs.AIcited by 0

On the map: LLM reasoning → Reasoning for agents, planning and code

Abstract (arXiv)

Across audit applications, judgments must be supported by reasonable evidence. However, standard financial language models prioritize fluency over evidence. They are built for general financial reasoning and may produce plausible but ambiguous answers, creating a grounding gap that makes them unsuitable for audit work. We address this gap with VERA-8B, a new end-to-end audit reasoning system that identifies audit risks before enforcement actions occur. Constructing such a model raises several challenges, as no prior machine learning work targets pre-enforcement audit prediction. To our knowledge, we are the first to unify SFT and GRPO for evidence-grounded audit reasoning under one evidence standard, achieving performance that surpasses all evaluated baselines. Because auditing cannot tolerate unsupported claims, we introduce abstention and uncertainty qualification to defer uncertain or evidence-incomplete cases. Finally, we design an AuditBridge to ground model reasoning for practical audit work. It transforms raw filings into verified records and then into reviewer-ready reports, bridging finance and computation with broad generality. Together, these components produce auditable, review-ready outputs suitable for practical audit work.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 13 of its 26 references that are in the map. First posted on arXiv 28 Aug 2026.

Builds on

13 of 26 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025Fin-R1: A Large Language Model for Financial Reasoning through Reinforcement Learning20 Mar
  2. 2025Fino1: On the Transferability of Reasoning-Enhanced LLMs and Reinforcement Learning to Finance12 Feb

Other references · 11

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  2. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 8,851
  3. 2017On Calibration of Modern Neural Networkscited by 4,860
  4. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,355
  5. 2017Selective Classification for Deep Neural Networkscited by 799
  6. 2021FinQA: A Dataset of Numerical Reasoning over Financial Datacited by 552
  7. 2020FinBERT: A Pretrained Language Model for Financial Communicationscited by 161
  8. 2025FinAuditing: A Financial Taxonomy-Structured Multi-Document Benchmark for Evaluating LLMscited by 14
  9. 2023Financial misstatement detection: a realistic evaluationcited by 4
  10. 2026AuditFraudBench: Benchmarking Audit Judgment in Detecting Fraudulent Misstatementscited by 3
  11. 2025AuditAgent: Expert-Guided Multi-Agent Reasoning for Cross-Document Fraudulent Evidence Discoverycited by 1

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  1. 2026FinRule-Bench: A Benchmark for Joint Reasoning over Financial Tables and Principles
  2. 2026FinRiskAtlas: Decision-Aligned Evaluation of Large Language Models for Financial Risk Review
  3. 2026AUDITFLOW: Executable Symbolic Environments for Structured Financial Reporting Verification
  4. 2026FinRCA-Bench: Benchmarking Evidence Retrieval and Reasoning for Financial AI Systems
  5. 2026FinGround: Detecting and Grounding Financial Hallucinations via Atomic Claim Verification
  6. 2026Code-as-Auditor: Executable Compliance Reasoning via Regulation-to-Code
  7. 2026E2A-Bench: Benchmarking Evidence-to-Action Reliability in Financial Chart Reasoning
  8. 2024FinDVer: Explainable Claim Verification over Long and Hybrid-Content Financial Documents