The latent factors of money laundering risk: A cross-national study

Author: 
Date created: 
2020-12-15
Identifier: 
etd21220
Keywords: 
Anti-money Laundering
Money Laundering
Structural Equation Modelling
Confirmatory Factor Analysis
Crime
Risk
Abstract: 

I present a new perspective on ‘money laundering,’ understanding it from a risk perspective using confirmatory factor analysis (CFA). I initially discuss the models studied so far in the money laundering and anti-money laundering literature, pointing out their shortcomings. I then set up my CFA model to identify the hidden factors of money laundering risk using observed variables across 203 countries. I compare my model with a competing data configuration proposed by the Basel Institute on Governance. I present a comprehensive application of CFA to understand how to combat money laundering risk and touch on the role of structural equation modelling in anti-money laundering policy-making. Using this method, I illustrate the hidden dimensions of money laundering risk. My findings will be useful for anti-money laundering policy experts around the world.

Document type: 
Graduating extended essay / Research project
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
File(s): 
Supervisor(s): 
Anil Hira
Department: 
Arts & Social Sciences: Department of Political Science
Thesis type: 
(Project) M.A.
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