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Natural Language Processing for Financial Regulation

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  • Ixandra Achitouv
  • Dragos Gorduza
  • Antoine Jacquier

Abstract

This article provides an understanding of Natural Language Processing techniques in the framework of financial regulation, more specifically in order to perform semantic matching search between rules and policy when no dataset is available for supervised learning. We outline how to outperform simple pre-trained sentences-transformer models using freely available resources and explain the mathematical concepts behind the key building blocks of Natural Language Processing.

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  • Ixandra Achitouv & Dragos Gorduza & Antoine Jacquier, 2023. "Natural Language Processing for Financial Regulation," Papers 2311.08533, arXiv.org.
    • Handle: RePEc:arx:papers:2311.08533
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    1. Scott Deerwester & Susan T. Dumais & George W. Furnas & Thomas K. Landauer & Richard Harshman, 1990. "Indexing by latent semantic analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 391-407, September.
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