Abstract

The purpose of this book is to introduce the reader to mechanisms useful for detection and avoidance of money-laundering activities (MLAs) and terrorist financing and suggest improvements to existing MLAs where appropriate.

Money laundering may occur in every country. The significant factor is to diagnose the illegal MLA and apply regulations to mitigate them. To meet this objective, managers of financial institutions need to train their employees about anti-money laundering (AML) processes and how to diagnose and prevent money laundering.

AML activities can also affect the financial systems of a country. “Money laundering destabilizes the foundation of a nation’s financial system by reducing tax revenues and impeding fair competition by ultimately disrupting economic development” (World Compliance, 2008). MLAs can create a big gap between income classes. Money laundering can also decrease banks’ or financial institutions’ credibility.

“In practice, criminals are trying to disguise the origins of money obtained through illegal activities so that it looks like it was obtained from legal sources” (Layton, 2005).

This book may be of special interest to financial managers in the private and public sector. It also may be a useful guide for those involved in international financial transactions.

Keywords

logistic regression, model building, model diagnostics, multiple regression, regression model, simple linear regression, statistical inference, time series regression

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