arxiv: 2604.05966 · v1 · submitted 2026-04-07 · 💻 cs.CL

Recognition: no theorem link

FinReporting: An Agentic Workflow for Localized Reporting of Cross-Jurisdiction Financial Disclosures

Fan Zhang , Mingzi Song , Rania Elbadry , Yankai Chen , Shaobo Wang , Yixi Zhou , Xunwen Zheng , Yueru He

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Yuyang Dai Georgi Georgiev Ayesha Gull Muhammad Usman Safder Fan Wu Liyuan Meng Fengxian Ji Junning Zhao Xueqing Peng Jimin Huang Yu Chen Xue (Steve) Liu Preslav Nakov Zhuohan Xie

Authors on Pith no claims yet

Pith reviewed 2026-05-10 19:27 UTC · model grok-4.3

classification 💻 cs.CL

keywords financial reportingcross-jurisdictionagentic workflowcanonical ontologylarge language modelsXBRLfinancial disclosuresanomaly logging

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The pith

FinReporting builds a unified canonical ontology and uses LLMs as constrained verifiers to align financial disclosures across US, Japan, and China regimes.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper introduces FinReporting as an agentic workflow that addresses cross-jurisdiction financial reporting by constructing a single canonical ontology covering Income Statement, Balance Sheet, and Cash Flow. It decomposes the task into explicit stages of filing acquisition, extraction, canonical mapping, and anomaly logging, treating LLMs strictly as evidence-grounded verifiers under decision rules rather than free-form generators. Evaluation on annual filings from the US, Japan, and China shows gains in consistency where taxonomies, tagging formats like XBRL versus PDF, and aggregation rules differ. A sympathetic reader would care because global investors, auditors, and regulators need reliable, comparable data without manual reconciliation across markets.

Core claim

FinReporting constructs a unified canonical ontology over the core financial statements and decomposes reporting into auditable stages that deploy large language models as constrained verifiers under explicit rules and evidence grounding, thereby improving consistency and reliability when applied to heterogeneous annual filings from the US, Japan, and China.

What carries the argument

The unified canonical ontology over Income Statement, Balance Sheet, and Cash Flow that performs semantic alignment across jurisdiction-specific taxonomies, combined with the staged agentic workflow that restricts LLMs to verification roles.

If this is right

Enables structured export and cross-market inspection of localized financial statements through the released interactive demo.
Handles variations in XBRL, PDF tagging, and aggregation by logging anomalies at each stage.
Reduces reliance on free-form LLM generation in favor of rule-constrained verification for financial data.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

If the ontology scales without distortion, the workflow could support automated compliance checks for multinational filings beyond the three tested markets.
Constraining LLMs to verification stages may lower hallucination rates when extracting numerical and categorical data from unstructured documents.
The staged design suggests a template for applying similar agentic pipelines to other domains with heterogeneous regulatory formats, such as ESG or tax disclosures.

Load-bearing premise

A single unified canonical ontology can be constructed that faithfully captures structural differences in accounting taxonomies, tagging infrastructures, and aggregation conventions across jurisdictions without material loss or distortion of meaning.

What would settle it

Running the system on a new set of filings from a fourth jurisdiction such as the EU and measuring whether key line items map accurately into the ontology without systematic anomalies or the need for manual overrides.

Figures

Figures reproduced from arXiv: 2604.05966 by Ayesha Gull, Fan Wu, Fan Zhang, Fengxian Ji, Georgi Georgiev, Jimin Huang, Junning Zhao, Liyuan Meng, Mingzi Song, Muhammad Usman Safder, Preslav Nakov, Rania Elbadry, Shaobo Wang, Xueqing Peng, Xue (Steve) Liu, Xunwen Zheng, Yankai Chen, Yixi Zhou, Yu Chen, Yueru He, Yuyang Dai, Zhuohan Xie.

**Figure 2.** Figure 2: The FinReporting demo interface. The system supports cross-jurisdiction statement browsing and reporting (US/JP/CN), with specific interested fields selected. and conversational extensions (Chen et al., 2021; Zhu et al., 2021; Chen et al., 2022; Xie et al., 2025; Qian et al., 2025b), as well as retrieval-centric longform settings, e.g., FinTextQA (Chen et al., 2024). In parallel, finance-oriented foundati… view at source ↗

**Figure 3.** Figure 3: Overview of FinReporting processes. porting logic. In contrast to existing XBRL-centric or single-market extraction pipelines that assume fixed taxonomies and homogeneous infrastructures, FinReporting explicitly models cross-jurisdiction heterogeneity and embeds structured verification into the reporting workflow, enabling auditable localization across heterogeneous filing regimes. 3 FinReporting System F… view at source ↗

read the original abstract

Financial reporting systems increasingly use large language models (LLMs) to extract and summarize corporate disclosures. However, most assume a single-market setting and do not address structural differences across jurisdictions. Variations in accounting taxonomies, tagging infrastructures (e.g., XBRL vs. PDF), and aggregation conventions make cross-jurisdiction reporting a semantic alignment and verification challenge. We present FinReporting, an agentic workflow for localized cross-jurisdiction financial reporting. The system builds a unified canonical ontology over Income Statement, Balance Sheet, and Cash Flow, and decomposes reporting into auditable stages including filing acquisition, extraction, canonical mapping, and anomaly logging. Rather than using LLMs as free-form generators, FinReporting deploys them as constrained verifiers under explicit decision rules and evidence grounding. Evaluated on annual filings from the US, Japan, and China, the system improves consistency and reliability under heterogeneous reporting regimes. We release an interactive demo supporting cross-market inspection and structured export of localized financial statements. Our demo is available at https://huggingface.co/spaces/BoomQ/FinReporting-Demo . The video describing our system is available at https://www.youtube.com/watch?v=f65jdEL31Kk

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

FinReporting gives a usable agentic pipeline for cross-border financial report alignment with LLMs as verifiers, but its claims rest on unquantified improvements.

read the letter

FinReporting gives a usable agentic pipeline for cross-border financial report alignment with LLMs as verifiers, but its claims rest on unquantified improvements. The paper lays out a multi-stage workflow that acquires filings, extracts data, maps items to a shared canonical ontology covering Income Statement, Balance Sheet, and Cash Flow, and logs anomalies. It restricts LLMs to constrained verification steps with explicit rules and evidence checks rather than open generation. That structure is the main practical contribution, and the release of an interactive demo plus video makes it easy to inspect outputs for US, Japan, and China filings. The engineering choices around auditability and jurisdiction-specific handling address a real pain point for anyone comparing reports across markets. The ontology and verifier approach is a reasonable way to reduce drift compared with naive prompting. The soft spots are in the evaluation and the ontology construction. The abstract states that the system improves consistency and reliability, yet supplies no error rates, baselines, ablations, or inter-annotator checks. The stress-test concern about the unified ontology distorting local accounting semantics holds weight here: US GAAP, J-GAAP, and Chinese standards differ in revenue recognition, segment reporting, and line-item aggregation, and without shown fidelity tests or expert validation the mappings could silently alter meaning. The full text would need to include the ontology schema and any quantitative results to move past this. This paper is for applied researchers or fintech teams who need traceable cross-market extraction tools. A reader focused on LLM workflows in regulated domains will find the pipeline design and demo useful even if the performance numbers are missing. It deserves peer review because the problem is concrete and the workflow is reproducible enough to test, though referees will need to see metrics and ontology details before the claims can be accepted.

Referee Report

2 major / 2 minor

Summary. The manuscript presents FinReporting, an agentic workflow for localized cross-jurisdiction financial reporting. It constructs a unified canonical ontology over Income Statement, Balance Sheet, and Cash Flow statements, decomposes the process into auditable stages (filing acquisition, extraction, canonical mapping, anomaly logging), and deploys LLMs as constrained verifiers under explicit decision rules rather than free-form generators. The system is evaluated on annual filings from the US, Japan, and China and claims to improve consistency and reliability under heterogeneous reporting regimes; an interactive demo is released.

Significance. If the central claims hold, the work could be significant for financial NLP by providing a structured, auditable approach to cross-border disclosure alignment where single-market assumptions fail. The emphasis on constrained verification and the release of a public demo are strengths that support reproducibility and practical adoption. However, the absence of any quantitative metrics, baselines, or ablation results makes it difficult to gauge the magnitude or reliability of the reported improvements.

major comments (2)

[Abstract] Abstract: the central claim that the system 'improves consistency and reliability' is unsupported by any quantitative metrics, baselines, error rates, ablation studies, or statistical comparisons. This is load-bearing because the evaluation is presented solely as a qualitative assertion without evidence that the workflow actually outperforms existing methods or maintains fidelity across regimes.
[Abstract] Abstract (ontology construction): the unified canonical ontology is asserted to map Income Statement, Balance Sheet, and Cash Flow items across US GAAP, J-GAAP, and Chinese standards, but no schema, mapping rules, fidelity checks, or validation against jurisdiction experts are described. This risks systematic distortion of semantics (e.g., differences in revenue recognition or segment reporting) and directly undermines the 'localized' and 'improved reliability' claims.

minor comments (2)

The demo URL and video link are helpful; consider adding a brief description of the demo's functionality and data coverage in the text.
Clarify the specific LLM models, prompting strategies, and exact decision rules used for the verifier agents, as these details are essential for reproducibility.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback and for recognizing the potential significance of FinReporting for cross-jurisdiction financial NLP. We agree that the current version would benefit from stronger quantitative support and more explicit documentation of the ontology to substantiate the claims of improved consistency, reliability, and localization.

read point-by-point responses

Referee: [Abstract] Abstract: the central claim that the system 'improves consistency and reliability' is unsupported by any quantitative metrics, baselines, error rates, ablation studies, or statistical comparisons. This is load-bearing because the evaluation is presented solely as a qualitative assertion without evidence that the workflow actually outperforms existing methods or maintains fidelity across regimes.

Authors: We agree that the abstract's claim lacks quantitative backing in the submitted version, where evaluation is demonstrated primarily via the workflow description, auditable stages, and public demo rather than numerical results. This is a substantive limitation. In the revised manuscript we will add quantitative metrics (e.g., mapping accuracy and cross-jurisdiction consistency scores on the US, Japan, and China filings), baselines (standard LLM extraction pipelines), error rates, and ablation studies isolating the constrained verifier agents. These additions will directly support the reliability claims. revision: yes
Referee: [Abstract] Abstract (ontology construction): the unified canonical ontology is asserted to map Income Statement, Balance Sheet, and Cash Flow items across US GAAP, J-GAAP, and Chinese standards, but no schema, mapping rules, fidelity checks, or validation against jurisdiction experts are described. This risks systematic distortion of semantics (e.g., differences in revenue recognition or segment reporting) and directly undermines the 'localized' and 'improved reliability' claims.

Authors: The full manuscript outlines the ontology construction within the canonical mapping stage, but we acknowledge that explicit schema details, mapping rules, fidelity checks, and expert validation are not presented with sufficient clarity or prominence. This weakens the localization argument. We will revise the abstract to note the ontology validation process and expand the main text with the schema structure, example mappings, semantic fidelity checks, and any expert review steps performed. This will address risks of semantic distortion while preserving the workflow focus. revision: yes

Circularity Check

0 steps flagged

No circularity: implemented workflow with no derivations or self-referential reductions

full rationale

The paper presents FinReporting as an agentic workflow that constructs a unified canonical ontology and decomposes reporting into stages (acquisition, extraction, mapping, anomaly logging) using LLMs as constrained verifiers. No equations, fitted parameters, predictions, or derivations are described that could reduce to their own inputs by construction. The evaluation on US, Japan, and China filings is framed as empirical results from the implemented system rather than a self-referential claim. No load-bearing self-citations, uniqueness theorems, or ansatzes are invoked; the central claims rest on the workflow design and demo, which are self-contained and externally inspectable via the released interactive demo.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the domain assumption that a canonical ontology can be built without loss and that LLMs can be reliably constrained as verifiers; no free parameters or new invented entities are introduced.

axioms (1)

domain assumption A unified canonical ontology can represent the core elements of Income Statement, Balance Sheet, and Cash Flow across US, Japanese, and Chinese reporting regimes.
The system is built around constructing and using this ontology as the mapping target.

pith-pipeline@v0.9.0 · 5601 in / 1266 out tokens · 54199 ms · 2026-05-10T19:27:32.628558+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

2 extracted references · 2 canonical work pages · 1 internal anchor

[1]

Published: 2024-03-27

https://www.ifrs.org/issued-standar ds/ifrs-taxonomy/ifrs-accounting-taxonom y-2024/. Published: 2024-03-27. Accessed: 2026- 02-26. Subhendu Khatuya. 2024. Parameter efficient instruc- tion tuning of llms for financial applications. InPro- ceedings of the Thirty-Third International Joint Con- ference on Artificial Intelligence, IJCAI-24, pages 8494–8495. ...

work page arXiv 2024
[2]

Bloomberggpt: A large language model for finance.CoRR, abs/2303.17564. Qianqian Xie, Weiguang Han, Zhengyu Chen, Ruoyu Xiang, Xiao Zhang, Yueru He, Mengxi Xiao, Dong Li, Yongfu Dai, Duanyu Feng, Yijing Xu, Haoqiang Kang, Ziyan Kuang, Chenhan Yuan, Kailai Yang, Zheheng Luo, Tianlin Zhang, Zhiwei Liu, Guojun Xiong, Zhiyang Deng, Yuechen Jiang, Zhiyuan Yao, ...

work page internal anchor Pith review arXiv 2024