How Data Can Be Applied in Regulation and Compliance

Data-driven decision-making leaves less space for error and is heavily applied in organizations that are able to leverage available to them data. Even though there are plenty of tools nowadays to analyze data, the principle GIGO is always there. Regardless of what software can do with data, the outcome has no value unless the application and the questions asked are correct. Data, however, is permanently a golden mine for those who can work with it. And one of the interesting areas where data can have a significant impact is the recently emerged RegTech.

Regulations and compliance have always been a pain point for businesses and large institutions as the regulatory bodies grew in number and complexity. The regulatory environment for financial institutions is especially hostile and creates sizable obstacles for banks to innovate. Strict compliance rules related to handling financial data don’t leave much space for maneuvering and restrict the opportunities related to insights that could have been derived from all the data available to organizations.

However, regulatory bodies could actually benefit themselves from data. Simplification and automation could put RegTech on a whole new level by harmonizing financial regulation across jurisdictions and creating new automated reporting and analytics standards. One of the first countries to start applying data-driven decision-making in compliance and regulation can be the UK as the government puts efforts in exploring application opportunities.

Regulatory policy modeling is one of the applications where techniques like agent-based modeling are believed to improve legislation. Governments often lack the vision of the whole range of implications certain regulatory requirements may result in. Hence, sometimes, policies that seem beneficial on paper don’t pass the reality check after they are applied in legislation. As an outcome, businesses and regulatory bodies face misunderstanding and the necessity to fix the situation. Some of the examples brought for the European region are MiFID II and EU FTT.

Developing common reporting standards across multiple jurisdictions may be able to bring together standardized data from different economies and oblige countries to share valuable information on successful regulatory policies and their implications across systems. Transparency and data sharing can help countries to learn from experiences and results of policies applied in other economies. If FinTech was to collaborate with regulators, new types and ways to collect and store data could be developed. For example, storing location data along with transactional data.

In fact, data sharing can not only help to improve the regulatory environment but also help governments to keep track of the activities that national financial institutions perform abroad. National regulatory bodies would be able to track possible illegal activities international companies perform in different markets and tighten the screws on those areas domestically.

Sophisticated mathematical techniques applied to data can yield possible risks. Hence, systemic risk tools can empower regulators with more accurate risks related to certain policies.

The integration and standardization of data collection and storage can aid businesses in simplifying the understanding of the regulatory environment on national and regional levels. International expansion and compliance with local requirements would be much more understandable for financial institutions from the regulatory perspective. In that case, there would be no necessity to invest significant resources in legal departments in different countries and instead, allocate them to the growth and enhancement of services.

RegTech can see a significant boost and enhancement in technology as regulators will soon need and invest in the development of open-source compliance tools to analyze data. For the emerging RegTech, it can be a golden ticket to governmental support for both regulatory and financial services.