IIF Authors

Status: Will be live at 03/13/2023 10:00

Data Policy Impacts - AML and Regtech Solutions

The case studies in this paper provide an overview of short form use-cases that we have encountered where organizations have made use of advanced technology to meet regulatory requirements in new and interesting ways. The case studies are intended to illustrate how anti-money laundering and other regtech solutions are impacted (positively and negatively) by data policies, including data localization measures and other data barriers.

Advanced compliance solutions, sometimes referred to as regtech, enable new ways for financial institutions (FIs) to service customers and conduct business activities in a compliant manner, while achieving operational improvement and cost efficiency. They provide for new ways for FIs to address regulatory requirements and fulfil regulatory objectives.

Regtech solutions, like many digital systems implemented by FIs today, are increasingly reliant on new technologies, particularly cloud computing, artificial intelligence (AI) and advanced data analytics. By their nature such technologies are data-hungry, and their effectiveness can be impaired when high-quality, timely data is less available. Compliance and other costs to FIs, as well as cyber or other operational risk can increase, and such costs can be passed on to consumers. Financial inclusion can be damaged if models are less accurate and predictive.

This paper is the second in a new series continuing the IIF's previous work on the costs of data localization and the state of and prospects for digital economic cooperation. This series is continuing with the addition of three case examples sharing tangible impacts and real-world trade-offs in fraud prevention, regulatory technology (regtech) and anti-money laundering (AML), and travel insurance. Exploring the impacts of data policy in these areas comes as the G7 appears poised to revisit the importance of data flows against a backdrop of the continued proliferation of restrictive data policies. We hope that they will trigger further reflection on the possible costs and potential for better solutions.