{"title":"NLP for Crypto-Asset Regulation: A Roadmap","authors":"Carolina Camassa","doi":"arxiv-2310.10333","DOIUrl":null,"url":null,"abstract":"In the rapidly evolving field of crypto-assets, white papers are essential\ndocuments for investor guidance, and are now subject to unprecedented content\nrequirements under the EU's Markets in Crypto-Assets Regulation (MiCAR).\nNatural Language Processing can serve as a powerful tool for both analyzing\nthese documents and assisting in regulatory compliance. This paper delivers two\ncontributions to the topic. First, we survey existing applications of textual\nanalysis to unregulated crypto-asset white papers, uncovering a research gap\nthat could be bridged with interdisciplinary collaboration. We then conduct an\nanalysis of the changes introduced by MiCAR, highlighting the opportunities and\nchallenges of integrating NLP within the new regulatory framework. The findings\nset the stage for further research, with the potential to benefit regulators,\ncrypto-asset issuers, and investors.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"73 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - General Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2310.10333","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the rapidly evolving field of crypto-assets, white papers are essential
documents for investor guidance, and are now subject to unprecedented content
requirements under the EU's Markets in Crypto-Assets Regulation (MiCAR).
Natural Language Processing can serve as a powerful tool for both analyzing
these documents and assisting in regulatory compliance. This paper delivers two
contributions to the topic. First, we survey existing applications of textual
analysis to unregulated crypto-asset white papers, uncovering a research gap
that could be bridged with interdisciplinary collaboration. We then conduct an
analysis of the changes introduced by MiCAR, highlighting the opportunities and
challenges of integrating NLP within the new regulatory framework. The findings
set the stage for further research, with the potential to benefit regulators,
crypto-asset issuers, and investors.