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Ever since the 2008 financial crisis shook the globe, regulations have and will continue to transform the financial industry. A part of this transformation is the adjacent and growing application of technology to meet complex regulatory challenges, particularly considering 2018 will see a host of regulations come into effect. These regulations will create a “perfect storm” of regulatory change and have an active part in disrupting the financial industry and inciting innovation. On the technology side, technologies that at the forefront of regtech include artificial intelligence (AI) and machine learning (ML).
Regtech has multiple, varying definitions that all deal with technology being used to meet regulatory challenges. An acceptable definition could characterize regtech as technology that helps solve regulatory challenges by providing governance, risk management, compliance and regulatory reporting solutions.
Specifically, those who provide financial services can benefit from implementing regtech solutions in a number of ways. For example, institutions can improve their understanding of how regulation impacts their business, support implementation and compliance, meet business demand through supplying digital-first products and services, decrease compliance and risk costs, increase organizational agility, and create better insight and oversight of compliance and risk management for customers and employees.
2018 is an important year for regtech, with a range of regulations coming into effect. The major regulations for 2018 are the Revised Payments Services Directive (PSD2), the General Data Protection Regulation (GDPR), and the second Markets in Financial Instruments Directive (MiFIDII), with PSD2 having an extended implementation schedule in the Netherlands and other EU countries.
As is the case in many industries, technology drives advances in how institutions do business, both in terms of internal and external practices. With regtech, we see that AI and ML are major technologies changing the way institutions tackle compliance and risk and analyse data, even though they are currently being developed to find the best and most efficient uses in regtech.
Although AI has been around for an extended period of time, it has primarily been used for non-governance risk and compliance (GRC) applications. However, its current use is being expanded to cover GRC processes, making them more sophisticated. Specifically, it is used in the analysis of regulations, pattern recognition, communications monitoring, and capturing information.
While improved use of analytic tools will make use of available big data, there is much potential for the use of Machine Learning (ML) to enhance the use of AI in regtech. Although these systems are being developed, large scale deployment and integration is still to come.
While young, regtech is becoming a key aera
As the regulatory landscape becomes growingly complex, stakeholders will have to leverage technology to maintain order within such a dynamic ecosystem. The marks of previous financial crisis, compliance costs, and innovation issues motivate the development of a regulatory systems placing as much as possible human out of the equation and modelling a common language within the regulatory environment.