Language Modeling for the Future of Finance: A Survey into Metrics, Tasks, and Data Opportunities

• URL: http://arxiv.org/abs/2504.07274v3
• Date: Tue, 14 Oct 2025 15:39:10 GMT
• Title: Language Modeling for the Future of Finance: A Survey into Metrics, Tasks, and Data Opportunities
• Authors: Nikita Tatarinov, Siddhant Sukhani, Agam Shah, Sudheer Chava,
• Abstract summary: Recent advances in language modeling have led to a growing number of papers related to finance in top-tier Natural Language Processing venues.<n>We review 374 NLP research papers published between 2017 and 2024 across 38 conferences and workshops, with a focused analysis of 221 papers that directly address finance-related tasks.
• Score: 6.024100148954438
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recent advances in language modeling have led to a growing number of papers related to finance in top-tier Natural Language Processing (NLP) venues. To systematically examine this trend, we review 374 NLP research papers published between 2017 and 2024 across 38 conferences and workshops, with a focused analysis of 221 papers that directly address finance-related tasks. We evaluate these papers across 11 quantitative and qualitative dimensions, and our study identifies the following opportunities for NLP researchers: (i) expanding the scope of forecasting tasks; (ii) enriching evaluation with financial metrics; (iii) leveraging multilingual and crisis-period datasets; and (iv) balancing PLMs with efficient or interpretable alternatives. We identify actionable directions supported by dataset and tool recommendations, with implications for both the academia and industry communities.

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