Teh Sin Yin - School of Management, Universiti Sains Malaysia, ۱۱۸۰۰ Minden, Penang, Malaysia.
Chang Yun Fah - Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Jalan Sg. Long, Cheras, ۴۳۰۰۰ Kajang, Selangor D.e
Wong Voon Hee - Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Jalan Sg. Long, Cheras, ۴۳۰۰۰ Kajang, Selangor D. E.
Ee Jia Wen - Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Jalan Sg. Long, Cheras, ۴۳۰۰۰ Kajang, Selangor D. E.

Financial organisation (i.e. bank) is constantly looking at method improving fraud detection to detect and stop the highest-risk transactions. This paper presents a Statistical Quality Control (SQC) approach, i.e. Shewhart X control chart for suspicious banking transaction detection based on bank indicator rules and control chart rules. One millionbank transaction records performed by 2000 accounts have been simulated. There are a total of 150 accounts randomly selected with 50 of them being indicated as suspicious transactions accounts. Two types of transaction records (i.e.deposit and withdrawal) were plotted on the Shewhart X chart in pair. A banking transaction is marked as suspicious when the chart indicates a matching pattern with bank indicator rule or the control chart rule. There are 45 out of the 50 accounts correctly detected as suspicious with 90% of sensitivity and 100% of specificity. Overall, the new method effectively detects suspicious transactions and improve client risk profiling.

suspicious transaction, SQC, control chart, sensitivity, specificity