RO-FIN-LLM: A Benchmark with LLM-as-a-Judge and Human Evaluators for Romanian Tax and Accounting

Large Language Models (LLMs) are increasingly being adopted in business settings; however, there remains a shortage of evaluation tools that account for country-specific regulations, particularly for Romania’s taxation and financial accounting requirements. RO-FIN-LLM is a benchmark designed to test how well LLMs handle Romania-specific regulatory question answering in taxation (including VAT regimes, income/profit tax, microenterprise rules, and other obligations) and financial accounting (including journal entries/monographs, amortization, provisions, and foreign exchange transactions). The benchmark contains questions curated by experts, each including the applicable regulatory time frames and the legal sources for the answers. Evaluation is performed in two protocols: closed-book and open-book with Retrieval Augmented Generation (RAG), using Tavily Search API. Evaluation metrics are represented by rubrics, namely correctness, legal citation quality, and clarity/structure. A subset of answers produced by three models was additionally evaluated by 12 specialists in the financial-accounting domain. In this revision, we also describe a public release plan for the question schema, prompts, and evaluation scripts to support independent reproducibility.

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Publication Details

Journal
Systems
Published
2026-02-27
DOI
https://doi.org/10.3390/systems14030244
Primary Topic
Artificial Intelligence in Law
Type
article
Field-Weighted Citation Impact
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article

RO-FIN-LLM: A Benchmark with LLM-as-a-Judge and Human Evaluators for Romanian Tax and Accounting

Octavian Dospinescu, Cristian Simionescu, Ana-Maria Bores, Maria-Ecaterina Olariu et al.
Systems
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article

RO-FIN-LLM: A Benchmark with LLM-as-a-Judge and Human Evaluators for Romanian Tax and Accounting

Octavian Dospinescu, Cristian Simionescu, Ana-Maria Bores, Maria-Ecaterina Olariu, Răzvan Georgescu, Adrian Iftene, Vlad-Gabriel Buinceanu, Cezar Tudor
article en

Abstract

Large Language Models (LLMs) are increasingly being adopted in business settings; however, there remains a shortage of evaluation tools that account for country-specific regulations, particularly for Romania’s taxation and financial accounting requirements. RO-FIN-LLM is a benchmark designed to test how well LLMs handle Romania-specific regulatory question answering in taxation (including VAT regimes, income/profit tax, microenterprise rules, and other obligations) and financial accounting (including journal entries/monographs, amortization, provisions, and foreign exchange transactions). The benchmark contains questions curated by experts, each including the applicable regulatory time frames and the legal sources for the answers. Evaluation is performed in two protocols: closed-book and open-book with Retrieval Augmented Generation (RAG), using Tavily Search API. Evaluation metrics are represented by rubrics, namely correctness, legal citation quality, and clarity/structure. A subset of answers produced by three models was additionally evaluated by 12 specialists in the financial-accounting domain. In this revision, we also describe a public release plan for the question schema, prompts, and evaluation scripts to support independent reproducibility.

SystemsVol. 14(3)
Ştefan cel Mare University of Suceava (RO), Alexandru Ioan Cuza University (RO), Romanian Academy (RO)
Openalex Percentile: Top 44%
Artificial Intelligence in Law
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