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arXiv · 2605.27333

FinHarness: An Inline Lifecycle Safety Harness for Finance LLM Agents

Haoxuan Jia·Yang Liu·Bin Chong·Yingguang Yang·Yancheng Chen·Jiayu Liang·Qian Li·Hanning Lu·Kefu Xu·Hao Zheng·Chongyang Zhang·Hao Peng·Philip S. Yu
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Abstract

Finance LLM agents must simultaneously block prompt-induced unauthorized actions and approve legitimate multi-step business workflows. However, boundary filters often miss irreversible mid-trajectory tool calls, while post-hoc LLM judges perform auditing only after termination -- too late for intervention and at a computational cost that scales linearly with trace length. We present FinHarness, an inline safety harness that wraps a finance agent end-to-end with three components: a Query Monitor that fuses single-turn intent with cross-turn drift, a Tool Monitor that evaluates each prospective tool call, and a Cascade module that integrates per-step risk and adaptively routes verification between a lightweight and an advanced-tier LLM judge. Fired risk factors are re-injected into the agent input as ex-ante evidence, enabling the agent to refuse, re-plan, or approve on its own. On FinVault, routed FinHarness cuts ASR from 38.3% to 15.0% while largely preserving benign approval ($41.1\% \to 39.3\%$), and uses $4.7\times$ fewer advanced-judge calls than an always-advanced ablation.

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Haoxuan Jia, Yang Liu, Bin Chong, Yingguang Yang, Yancheng Chen, Jiayu Liang, Qian Li, Hanning Lu, Kefu Xu, Hao Zheng, Chongyang Zhang, Hao Peng, Philip S. Yu. 2026-05-26. FinHarness: An Inline Lifecycle Safety Harness for Finance LLM Agents. https://arxiv.org/abs/2605.27333

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