This book examines the interpretation of the risk-based approach (RBA) and its application across the banking industry. It explores the ways conflicting risk interpretation and deconstruction of money laundering risk have unintended consequences across the banking industry. Furthermore, it offers a theoretical framework that can be adopted and implemented by risk practitioners to address money laundering (ML) risks.

The interpretation and application of the RBA influences the way money laundering risk is perceived, presented, and managed, often resulting in misalignment among stakeholders. Moreover, AML practitioners interpret money laundering (ML) risk as an entity that can be contained, largely in ignorance of the fact that ML risk is self-referential.

The book therefore addresses complex inter-system feedback phenomena that lead to de-risking and re-risking, and offers a new ML risk communication framework on this basis. It will be of value to researchers and also to stakeholders within financial institutions, financial intelligence units and regulators in the fight against money laundering.

Equips readers with an innovative ML risk communication framework to enhance current processes Contains new sources of data collected within financial intelligence units Provides a theoretical framework for analyzing money laundering and terrorism financing

Autorentext

Noemi També Bearpark is an Associate Professor at the Luxembourg School of Business and the founder and director of Tambe advisory and consulting which delivers financial crime prevention, anti-money laundering, counter-terrorist financing and counter-proliferation finance systems and controls across the banking, non-profit and public sectors. Her academic research mainly focuses on anti-money laundering where she evaluates risk management and communication across organisations within the private and the public sector. She holds her PhD in Systems Studies from the Centre for Systems Studies, University of Hull, UK.

Klappentext

This book examines the interpretation of the risk-based approach (RBA) and its application across the banking industry. It explores the ways conflicting risk interpretation and deconstruction of money laundering risk have unintended consequences across the banking industry. Furthermore, it offers a theoretical framework that can be adopted and implemented by risk practitioners to address money laundering (ML) risks. The interpretation and application of the RBA influences the way money laundering risk is perceived, presented, and managed, often resulting in misalignment among stakeholders. Moreover, AML practitioners interpret money laundering (ML) risk as an entity that can be contained, largely in ignorance of the fact that ML risk is self-referential. The book therefore addresses complex inter-system feedback phenomena that lead to de-risking and re-risking, and offers a new ML risk communication framework on this basis. It will be of value to researchers and also to stakeholders within financial institutions, financial intelligence units and regulators in the fight against money laundering.

Inhalt
Chapter 1. Introduction to Anti-Money Laundering.- Chapter 2. Risk and Luhmann's Systems Theory.- Chapter 3. Case Studies and Empirical Findings.- Chapter 4. Analysis and Discussion.- Chapter 5. Conclusion.