The important factors of anti-money laundering and counter-terrorism financing education

• Main Authors: Redzuan, Nur Harena, Abd Rahman, Nur Hasnida, El-Muhammady, Ahmad
• Format: Conference or Workshop Item
• Language: English; English
• Published: International Islamic University Malaysia 2019
• Subjects: HG3368 Islamic Banking and Finance; HG4001 Financial management. Business finance. Corporation finance.
• Online Access: http://irep.iium.edu.my/73301/24/73301%20The%20Important%20Factors%20Influencing%20AML-CTF.pdf; http://irep.iium.edu.my/73301/1/Redzuan%2C%20Abd%20Rahman%2C%20Ahmad%20-%202019%20-%20Conference%20ICFM.pdf; http://irep.iium.edu.my/73301/

This paper aims to identify the important factors of anti-money laundering and counter-terrorism financing (AML/CTF) education for finance students in the higher learning institution in Malaysia. It relates between the factors of gender, the program of study either undergraduate or postgraduate studies, nationality either Malaysian or international students, age and lastly status of study either the full-time students or working students. The neural networks model analysis is used to answer the research questions based on 190 respondents of finance students in the higher learning institution in Malaysia. Data collection is conducted through a direct survey using a self-administrated questionnaire. The results from neural networks models demonstrate that gender is the most important factors that influence the knowledge of AML, while nationality is the most important factors that influence the awareness upon the CTF. The result also has shown that the status of study influences the opinion that AML/CTF education is important for finance students in the higher learning institution in Malaysia. This paper reveals the opinion from finance students in higher learning institution about AML/CFT education based on the factors of gender, the program of study either undergraduate or postgraduate studies, nationality either Malaysian or international students, age and lastly status of study either the full-time students or working students. Subsequently, this paper adopted a neural networks model to identify the key factors of AML/CFT education.