Policy making in the financial industry: A framework for regulatory impact analysis using textual analysis

Abstract

Abstract Regulators conduct regulatory impact analyses (RIA) to evaluate whether regulatory actions fulfill the desired goals. Although there are different frameworks for conducting RIA, they are only applicable to regulations whose impact can be measured with structured data. Yet, a significant and increasing number of regulations require firms to comply by specifying and communicating textual data to consumers and supervisors. Therefore, we develop a methodological framework for RIA in case of unstructured data following the design science research paradigm. The framework enables the application of textual analysis and natural language processing to assess the impact of regulatory actions that result in unstructured data and offers guidance on how to map suitable methods to the dimensions impacted by the regulation. We evaluate the framework by applying it to the European financial market regulation MiFID II, specifically the recent regulatory changes regarding best execution. Thereby, we show that MiFID II failed to improve informativeness and comprehensibility of best execution policies.

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