Research on money
laundering risk assessment of
customers – based on the
empirical research of China
Shan Xi Normal University, Lin Fen, China, and
Tai Yuan University of Science and Technology, Tai Yuan, China
Purpose – To implement a risk-based regulatory approach, this paper aims to make an assessment on
customers’ money laundering risk and conducts some applications.
Design/methodology/approach – During the transition of a regulatory approach from “rule-based”
to “risk-based”, this paper considers that the area of a customer, types of business and the industries to
which the customer belongs are the main indicators to judge money laundering risk of a customer.
Based on the statistical analysis of 221 typical money laundering cases, rst-class index weights are
given by using the entropy weight method and then by combining with the membership function, this
paper determines a customer’s money laundering risk levels. On the basis of the entropy weight method,
this paper uses the C5.0 algorithm to construct a decision tree model and then carries out application
research on customer money laundering risk assessment to verify the effectiveness of the entropy
weight method and the decision tree model.
Findings – This empirical research found the weights of three key money laundering indicators:
customer areas, business types and corresponding industries.
Originality/value – Asserting that current money laundering risk assessments of customers are
marginal at best, this paper contends from the perspective of practice, and applies the entropy weight
method and the decision tree model for money laundering risk assessment of customers.
Keywords China, Risk assessment, Decision tree, Entropy weight method,
Anti-money laundering (AML)
Paper type Research paper
1. Research background
China established its “rule-based” regulatory approach of anti-money laundering (AML)
in 2003, with numerous institutions and scholars studying and practicing the approach
concerning AML activities. Implemented over 10 years, on the one hand, a lot of
manpower, nances and resources were consumed to monitor money laundering
activities; however, on the other hand, the regulatory effectiveness is relatively low: a lot
The authors would like to thank Professor Yao-wen Xue for his professional advice and support
on this research. In addition, this paper was supported by the NSFC (NO. 71273159). Project name:
Analysis of illegal public ofcials’ money laundering and money laundering network topology.
The current issue and full text archive of this journal is available on Emerald Insight at:
Journalof Money Laundering
Vol.19 No. 3, 2016
©Emerald Group Publishing Limited