Data science trends in RegTech 2022

Demand for RegTech services inflated in 2021, and there is still a lot of potential for the industry to grow further. The importance of accessible, understandable, and consistent data for compliance reporting will push the industry to evolve rapidly.

At ACT RegTech Solutions, we consistently monitor and analyze the latest innovations in this field. It is clear that data and data science capabilities will grow significantly in 2022. This article will cover the trends that we believe will shape the coming year.

  1. Enabling unstructured data (NLP)
  2. Addressing Data Quality issues
  3. The rise of AutoML
  4. Surge in new RegTech tooling
  5. Holistic regulatory portfolio insight

1. Enabling unstructured data

Natural language processing (NLP) is continuing to take new shapes as different businesses discover valuable applications of artificial intelligence (AI) technology. NLP has gained a lot of momentum in the last few years. According to the 2021 Natural Language Processing (NLP) Industry Survey by John Snow Labs, growth has continued steadily, with 90% of tech leaders indicating that their NLP budgets have increased at least 10-30% over the last year.

Most of the generated and collected data is unstructured and therefore the importance of language models is growing significantly. NLP is now starting to play a role in our day-to-day lives, especially in customer engagement (e.g. with conversational AI such as chatbots). Over time underlying models will improve and achieve tasks like writing articles and generating reports in a natural, human manner.

2. Addressing DQ issues

Data has long been recognized as the source of tremendous possibilities. Yet, most of the data is only collected and stored for (often minimal) compliance purposes. Companies realize they are sitting on a potential gold mine but don’t know how to extract value from the data.

One of the main reasons companies struggle to extract value from their data is because the data quality is not up to par. We have seen initiatives in 2021 to improve data quality, this will only continue in the coming year. Big data and data-driven decision-making have become the new standard, but now the focus should not only be on gathering large quantities of data, but also on improving the quality. This will allow companies to derive more insights and make better-informed decisions.

3. The rise of autoML

Automated Machine Learning, or AutoML, is one of the latest trends in data science. A large part of the normal data science project consists of data preparation and cleansing. This is an essential but repetitive and time-consuming part of the data science lifecycle. AutoML helps to automate these mundane tasks and offers data scientists the opportunity to spend their time on more challenging/value-add matters.

Essentially, AutoML leverages automation for the application of machine learning models. The AutoML framework is growing and assists data scientists in data visualization, model deployment and can even accelerate the hyperparameter selection.

4. Surge in new RegTech tooling

According to The Business Research Company’s research report on the RegTech market, the RegTech industry has grown by approximately 26% in the last year. Especially, the rising number of fraudulent activities in the financial market has spawned many anti-money laundering (AML) and counter-terrorist funding (CTF) initiatives.

With a growing demand for RegTech solutions, the market has responded with increased supply. In fact, financial institutions now have an overflow of options to choose from. As such in 2022 financial institutions might find it increasingly harder to navigate the broad variety of solutions and find the right fit for their organizations. This makes it increasingly important to have sound operational processes in place that can be augmented and supported by the latest RegTech tooling.

5. Holistic regulatory portfolio insight

Regulatory change has been a constant in the financial services industry and will certainly remain an important topic of discussion. However, a change in attitude is visible. We notice a shift in the way regulatory and compliance projects are managed. Traditionally, regulatory tracks were set up and implemented as separate projects, with each team focusing on a single regulation. This is an inefficient approach to compliance, and firms have realized that single datasets can be used for multiple regulations. There is a need for integrated data capabilities and holistic insight in the regulatory portfolio to manage existing and future regulatory initiatives.

In 2022 the industry will continue to require compliance departments to evolve. Adapting new technologies will enable companies to improve their processes and gain better insights as they strive to obtain a holistic view across their entire regulatory portfolio. Companies that succeed to get a better grip are sure to flourish in 2022 and beyond.

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