Natural Language Processing for Financial Regulation

Ixandra Achitouv, Dragos Gorduza and Antoine Jacquier

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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.

Date: 2023-11
New Economics Papers: this item is included in nep-ain, nep-ban, nep-big, nep-cba and nep-cmp
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