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arXiv · 2509.09544

MetaGraph: A Large-Scale Meta-Analysis of GenAI in Financial NLP (2022-2025)

Paolo Pedinotti·Peter Baumann·Nathan Jessurun·Leslie Barrett·Enrico Santus
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Abstract

Financial NLP has evolved rapidly since late 2022, outpacing narrative surveys. We introduce MetaGraph, a methodology for extracting typed knowledge graphs from scientific corpora using ontology-guided LLM extraction to enable structured, large-scale trend analysis. Applied to 681 papers on GenAI in Finance (2022-2025), MetaGraph reveals three phases: early LLM-driven expansion of tasks and datasets, growing emphasis on limitations and risk, and a shift toward modular, system-oriented methods (e.g., retrieval-augmented designs). We release the resulting resource and artifacts to support reproducible meta-analysis and future monitoring of the field.

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Paolo Pedinotti, Peter Baumann, Nathan Jessurun, Leslie Barrett, Enrico Santus. 2025-09-11. MetaGraph: A Large-Scale Meta-Analysis of GenAI in Financial NLP (2022-2025). https://arxiv.org/abs/2509.09544

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