Decoding SEC Actions: Enforcement Trends through Analyzing Blockchain litigation using LLM-based Thematic Factor Mapping
This provides clarity on compliance risks for blockchain companies and investors, but it is incremental as it applies existing LLM methods to a new dataset of regulatory actions.
The study tackled the lack of systematic analysis of factors driving SEC litigation against blockchain entities by mapping all SEC complaints from 2012 to 2024 using LLMs to identify thematic factors and assess their influence on legal Acts, revealing regulatory patterns and trends.
The proliferation of blockchain entities (persons or enterprises) exposes them to potential regulatory actions (e.g., being litigated) by regulatory authorities. Regulatory frameworks for crypto assets are actively being developed and refined, increasing the likelihood of such actions. The lack of systematic analysis of the factors driving litigation against blockchain entities leaves companies in need of clarity to navigate compliance risks. This absence of insight also deprives investors of the information for informed decision-making. This study focuses on U.S. litigation against blockchain entities, particularly by the U.S. Securities and Exchange Commission (SEC) given its influence on global crypto regulation. Utilizing frontier pretrained language models and large language models, we systematically map all SEC complaints against blockchain companies from 2012 to 2024 to thematic factors conceptualized by our study to delineate the factors driving SEC actions. We quantify the thematic factors and assess their influence on specific legal Acts cited within the complaints on an annual basis, allowing us to discern the regulatory emphasis, patterns and conduct trend analysis.