AUTHOR COPY Journal of Intelligent & Fuzzy Systems 31 (2016) 805–813 DOI:10.3233/JIFS-169012 IOS Press 805 Fuzzy rule-based analysis of spatio-temporal ATM usage data for fraud detection and prevention 1 Ayhan Demiriz ∗ and Bet ¨ ul Ekizo ˘ glu Department of Industrial Engineering, Sakarya University, Sakarya, Turkey Abstract. This article presents a novel approach for detecting fraudulent behaviors from automated teller machine (ATM) usage data by analyzing geo-behavioral habits of the customers and describe the use of a fuzzy rule-based system capable of classifying suspicious and non-suspicious financial transactions. Firstly, the geographic entropies of ATM cardholders are computed from the spatio-temporal ATM transactions data to form customer classes of mobility. ATM transactions exhibit spatio-temporal properties by inclusion of location information. The transition data can be generated by using transaction data from the current location to the next one. Once, the transition data are generated, statistical outlier detection techniques can be utilized. On top of classical methods, crisp unsupervised methods can easily be used for detecting outliers in the transition data. In addition, fuzzy C-Means algorithm can be implemented to determine outliers. In this study, ATM usage dataset containing around two years’ worth of data, provided by a mid-size Turkish bank was analyzed. It was shown that a significant bulk of ATM users does not leave the vicinity of their living places. Some insightful business rules that can be extracted from geo-tagged ATM transaction data by means of using a fuzzy rule-based system were also presented. Keywords: Location intelligence, fraud detection, ATM fraud, spatio-temporal outlier 1. Introduction Bank customers across the globe enjoy the flexi- bility of being able to access their monetary assets whenever and wherever they need as much as the technology allows. But new fraud issues also present themselves and anonymity becomes easier with the new technologies. Ensuring the security of trans- actions carried out by banks and other financial institutions is one of the major factors affecting the reputation and profitability of such organiza- tions. Customers’ sense of trust and security are 1 This research is financially supported by Ministry of Science, Industry and Technology under Grant 519.STZ.2013-2. ∗ Corresponding author. Ayhan Demiriz, Department of Indus- trial Engineering, Sakarya University, 54187 Sakarya, Turkey. E-mail: ademiriz@gmail.com. fundamental requisites for the banks which typically manage customers’ money and personal information. As a result of widespread usage of alternative deliv- ery channels in the past few years, losses because of fraud transactions show a dramatic increase and so financial fraud detection and prevention have been receiving increasing attention [6]. Fraud detection activities involve monitoring the behavior of trans- actions while prevention means a proactive approach that involves the analysis of transactions before they are completed and identifying if they are fraud or not [6]. Automated teller machines (ATMs), which offer the consumers a quality of life by allowing them to access cash and other financial information, occupy an important position in alternative delivery channels of banking. Since the introduction of the first ATM in 1064-1246/16/$35.00 © 2016 – IOS Press and the authors. All rights reserved