14. How Technology (or Distributed Ledger Technology and Algorithms Like Deep Learning and Machine Learning) Can Help to Comply with Regulatory Requirements

An ever-increasing volume of data at financial institutions combined with a regulatory tsunami leads to problems that are difficult to solve with the current methods in order to meet the regulatory requirements. This article investigates how Distributed Ledger Technology (DLT), Artificial Intelligence (AI) and Machine Learning (ML) can open new horizons for the regulatory value chain and can be seen as possible cost reducers. The power of AI and ML is based on the data being used. In this article, we will take a closer look at how DLT could improve regulatory reporting quality and processes and what implications DLT can have for banks and regulators with respect to regulatory reporting. Moreover, it investigates how AI can support us in regulatory reporting, using MiFID 2 as an example. It discusses what risks can be mitigated for Anti Money Laundering (AML), Know Your Customer (KYC) and how the generic intelligent stress tests help to meet the minimum requirements. Lastly, it describes how natural language processing (NLP) can reduce the regulatory burden.