PIO at the FinEval 2026: An OpenRouter API Pipeline for Multilingual Financial Understanding

Israel Olanrewaju Odeajo

PIO at the FinEval 2026: An OpenRouter API Pipeline for Multilingual Financial Understanding

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Abstract

We present the PIO system for the FinEval 2026 / FinNLP Multilingual Financial Language Understanding Challenge. Our submission follows the API-based agent/workflow track: all model calls go through OpenRouter and use meta-llama/llama-3.3-70b-instruct (≈70.6B parameters). We address all three subtasks with task-specific pipelines that combine LLM prompting with high-precision rules and schema constraints. On the public leaderboard our scores are entity micro-F1 0.9748 (Greek NER), accuracy 0.9333 (Japanese ICR), and ROUGE-1 1.0000 (PolyFiQA). We describe the design choices behind each subtask, the failure modes we observed, and simple post-corrections that yielded large gains on Subtask 1.

Anthology ID:: 2026.finnlp-1.63
Volume:: Proceedings of the 11th Workshop on Financial Technology and Natural Language Processing
Month:: October
Year:: 2026
Address:: Budapest, Hungary
Editors:: Jimin Huang, Yongjae Lee, Sophia Ananiadou, Hsin-Hsi Chen, Hiroya Takamura, Chung-Chi Chen
Venues:: FinNLP | WS
SIG:: SIGFinTech
Publisher:: Association for Computational Linguistics
Note:
Pages:: 740–744
Language:
URL:: https://aclanthology.org/2026.finnlp-1.63/
DOI:
Bibkey:
Cite (ACL):: Israel Olanrewaju Odeajo. 2026. PIO at the FinEval 2026: An OpenRouter API Pipeline for Multilingual Financial Understanding. In Proceedings of the 11th Workshop on Financial Technology and Natural Language Processing, pages 740–744, Budapest, Hungary. Association for Computational Linguistics.
Cite (Informal):: PIO at the FinEval 2026: An OpenRouter API Pipeline for Multilingual Financial Understanding (Odeajo, FinNLP 2026)
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PDF:: https://aclanthology.org/2026.finnlp-1.63.pdf

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@inproceedings{odeajo-2026-pio,
    title = "{PIO} at the {F}in{E}val 2026: An {O}pen{R}outer {API} Pipeline for Multilingual Financial Understanding",
    author = "Odeajo, Israel Olanrewaju",
    editor = "Huang, Jimin  and
      Lee, Yongjae  and
      Ananiadou, Sophia  and
      Chen, Hsin-Hsi  and
      Takamura, Hiroya  and
      Chen, Chung-Chi",
    booktitle = "Proceedings of the 11th Workshop on Financial Technology and Natural Language Processing",
    month = oct,
    year = "2026",
    address = "Budapest, Hungary",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.finnlp-1.63/",
    pages = "740--744",
    ISBN = "979-8-89176-466-8",
    abstract = "We present the PIO system for the FinEval 2026 / FinNLP Multilingual Financial Language Understanding Challenge. Our submission follows the API-based agent/workflow track: all model calls go through OpenRouter and use meta-llama/llama-3.3-70b-instruct ($\approx$70.6B parameters). We address all three subtasks with task-specific pipelines that combine LLM prompting with high-precision rules and schema constraints. On the public leaderboard our scores are entity micro-F1 0.9748 (Greek NER), accuracy 0.9333 (Japanese ICR), and ROUGE-1 1.0000 (PolyFiQA). We describe the design choices behind each subtask, the failure modes we observed, and simple post-corrections that yielded large gains on Subtask 1."
}

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%0 Conference Proceedings
%T PIO at the FinEval 2026: An OpenRouter API Pipeline for Multilingual Financial Understanding
%A Odeajo, Israel Olanrewaju
%Y Huang, Jimin
%Y Lee, Yongjae
%Y Ananiadou, Sophia
%Y Chen, Hsin-Hsi
%Y Takamura, Hiroya
%Y Chen, Chung-Chi
%S Proceedings of the 11th Workshop on Financial Technology and Natural Language Processing
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-466-8
%F odeajo-2026-pio
%X We present the PIO system for the FinEval 2026 / FinNLP Multilingual Financial Language Understanding Challenge. Our submission follows the API-based agent/workflow track: all model calls go through OpenRouter and use meta-llama/llama-3.3-70b-instruct (\approx70.6B parameters). We address all three subtasks with task-specific pipelines that combine LLM prompting with high-precision rules and schema constraints. On the public leaderboard our scores are entity micro-F1 0.9748 (Greek NER), accuracy 0.9333 (Japanese ICR), and ROUGE-1 1.0000 (PolyFiQA). We describe the design choices behind each subtask, the failure modes we observed, and simple post-corrections that yielded large gains on Subtask 1.
%U https://aclanthology.org/2026.finnlp-1.63/
%P 740-744

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Markdown (Informal)

[PIO at the FinEval 2026: An OpenRouter API Pipeline for Multilingual Financial Understanding](https://aclanthology.org/2026.finnlp-1.63/) (Odeajo, FinNLP 2026)

PIO at the FinEval 2026: An OpenRouter API Pipeline for Multilingual Financial Understanding (Odeajo, FinNLP 2026)

ACL

Israel Olanrewaju Odeajo. 2026. PIO at the FinEval 2026: An OpenRouter API Pipeline for Multilingual Financial Understanding. In Proceedings of the 11th Workshop on Financial Technology and Natural Language Processing, pages 740–744, Budapest, Hungary. Association for Computational Linguistics.