Legal NLP Meets M i CAR : Advancing the Analysis of Crypto White Papers (2023)

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 European Union’s Markets in Crypto-Assets Regulation (MiCAR). Natural Language Processing (NLP) 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.

## introduction white papers are the cornerstone of information disclosure for initial coin offerings (icos), a modern fundraising method that sells tokens to a diverse group of investors @xcite . these fundraisings represent an alternative method for entrepreneurial finance, with similarities to ipos, venture capital, and presale crowdfunding @xcite . when a new ico is announced, it is usually accompanied by the white paper, a text document that contains information for the investors and bears some similarities, at least in intent, with an ipo prospectus. however, unlike their regulated counterparts, white papers have so far operated in a largely unregulated landscape. thanks to this regulatory vacuum, the type of content varies widely, but it usually includes @xcite a description of the service offered and its value proposition, the composition of the project team, financial details about the offer, and explanations of the technologies underlying the project. due to their public accessibility and richness in data, white papers have been a frequent subject of studies aimed at extracting market insights through textual analysis @xcite ; @xcite ; @xcite among others). the current ico market is characterized by a pronounced level of information asymmetry between crypto issuers and investors @xcite . these circumstances, easily explained by the lack of regulation, led to investigation into the prevalence of fraud and scams among icos @xcite . it is not uncommon for white papers to be a vehicle for misinformation, sometimes resorting to imprecise claims and exaggerated language (momtaz, 2021) to lure investors. ## how mica changes the regulatory landscape the mica regulation is broad and covers three categories of crypto assets: asset-referenced tokens, e-money tokens, and crypto assets other than foot_1 . the latter category also includes utility tokens, a specific type of crypto asset that has no financial purposes and is only intended to provide access to a good or a service supplied by its issuer. some types of crypto assets, such as non-fungible tokens (nfts), are not covered by the regulation. for each crypto asset category , the regulation contains norms regarding the content and issuance of the white paper, the conduct of business, in addition to organizational and financial requirements. in alignment with the objective of the study, the rest of the work will focus only on the norms for white paper content, and in particular those valid for the crypto "other than" category. while the requirements vary across the three asset categories, the differences are marginal in the scope of the analysis. another reason supporting this choice is the fact that the "other than" category has the largest set of requirements for white papers-see appendix a. ## conclusions crypto asset white papers are valuable data sources for nlp practitioners due to their public availability and rich informational content. the entry into force of the micar opens new avenues for nlp applications to assist various stakeholders, including regulators, issuers, and potential investors, in navigating compliance and regulatory oversight. our survey of existing literature on the textual analysis of white papers revealed an active but siloed field that could benefit significantly from interdisciplinary collaboration between computer science, finance, and legal experts. existing work in the legal nlp field could serve as a foundation for developing algorithms and models tailored to this new regulatory landscape. researchers have a clear opportunity to contribute to this emerging area, with the potential not only to streamline regulatory processes but also to create a more transparent and accountable crypto asset ecosystem.