TY - JOUR
T1 - A novel dynamic approach to identifying suspicious customers in money transactions
AU - Shaikh, Abdul Khalique
AU - Nazir, Amril
N1 - Publisher Copyright:
Copyright © 2020 Inderscience Enterprises Ltd.
PY - 2020
Y1 - 2020
N2 - Money laundering activity causes a negative impact on the development of the national economy. Anti-money laundering (AML) solutions within financial institutions facilitate to control it in a suitable way. However, one of the fundamental challenges in AML solution is to identify real suspicious transactions. To identify these types of transactions, existing research uses pre-defined rules and statistical approaches that help to detect the suspicious transactions. However, due to the fixed and predetermined rules, it is highly probable that a normal customer can be identified as suspicious customers. To overcome the above limitations, a novel dynamic approach to identifying suspicious customers in money transactions is proposed that is based on dynamic analysis of customer profile features to identify suspicious transactions. The experiment has been executed with real bank customers and their transactions data and the results of the experiment provide promising outcomes in terms of accuracy.
AB - Money laundering activity causes a negative impact on the development of the national economy. Anti-money laundering (AML) solutions within financial institutions facilitate to control it in a suitable way. However, one of the fundamental challenges in AML solution is to identify real suspicious transactions. To identify these types of transactions, existing research uses pre-defined rules and statistical approaches that help to detect the suspicious transactions. However, due to the fixed and predetermined rules, it is highly probable that a normal customer can be identified as suspicious customers. To overcome the above limitations, a novel dynamic approach to identifying suspicious customers in money transactions is proposed that is based on dynamic analysis of customer profile features to identify suspicious transactions. The experiment has been executed with real bank customers and their transactions data and the results of the experiment provide promising outcomes in terms of accuracy.
KW - AML
KW - Anti-money laundering
KW - Data analysis
KW - Dynamic AML analysis
KW - Money transaction
KW - Suspicious transactions
UR - http://www.scopus.com/inward/record.url?scp=85089371861&partnerID=8YFLogxK
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U2 - 10.1504/IJBIDM.2020.108762
DO - 10.1504/IJBIDM.2020.108762
M3 - Article
AN - SCOPUS:85089371861
SN - 1743-8187
VL - 17
SP - 143
EP - 158
JO - International Journal of Business Intelligence and Data Mining
JF - International Journal of Business Intelligence and Data Mining
IS - 2
ER -