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arXiv:2601.15322cs.AI

Replayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agents

Raffi Khatchadourian

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Abstract

Replaying a financial agent requires specifying the conditions of a rerun, preserving its execution record, and deciding which parts of its behavior to compare. We introduce the Determinism-Faithfulness Assurance Harness (DFAH), a framework and practical protocol for organizing these choices. The framework distinguishes comparisons of final decisions, tool-name sets, and ordered tool names, while treating support from available evidence as a separate evaluation target. We illustrate the framework using 2,957 recorded executions in synthetic compliance-triage and data-operations tasks. One data-operations configuration repeated its recorded decision across all trials on 84% of cases, while its ordered tool-name sequence repeated on 26%. Conversely, some compliance cases retained the same tool sequence while recorded decisions changed. A case-level example shows how repeated labels accompanied different lookups and escalation calls. These observations demonstrate how the comparison level changes the description of repeated behavior. The resulting protocol connects configuration control, preservation of each attempt, comparison of records, and inspection of changed cases. DFAH provides a practical foundation for designing replay experiments and locating execution differences during the development and evaluation of financial agents.

arXiv comments
12 pages, 2 figures, 5 tables. Replay framework and descriptive experiments in synthetic financial tasks. Includes an offline reproduction package. Original version accepted at the 2nd ICLR Workshop on Advances in Financial AI (2026)
Journal reference
DOI
Subjects
cs.AIArtificial Intelligence cs.CLComputation and Language

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    • Introed Determinism-Faithfulness assurance harness (DFAH) in new paper "Replayable Financial Agents" along with the open-source code A few findings: - Determinism and faithfulness are positively correlated (r = 0.45) for the tasks in my experiments - Schema-first Tier 1 (7–20B)…

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