Deconstructing Money Laundering Risk
De-risking, the Risk-based Approach and Risk Communication
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Beschreibung
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.
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
Autor*in
Noémi També Bearpark
Themen in »Deconstructing Money Laundering Risk«
Anti-money laundering Terrorism financing Compliance Regulation Systems theory Risk governance Financial institution Suspicious Activity Report (SAR) Money Laundering (ML) Financial action task force International monetary funds National risk assessment Financial intelligence unit Luhmann's system theory Human rights watch