Online Credit Card Fraud
Importance
Online credit card fraud happens when someone steals other’s credit card information to make purchases. The online credit card fraud is important because it is easier to fraud anonymously, or tracking someone over the internet and prosecuting them is complicated and requires technical knowledge. Online credit card fraud can hit anyone who makes their payments online. The problem is greater for digital products as credit card companies refuse to provide much needed protection to the sellers (Brabazon et al., 2007). As credit card transitions are prevalent for global payments, there have been increased cases of online credit card faults and subsequent losses for banks. Therefore, improving the online fraud detection is essential for maintaining the viability of the payment system. When banks start losing money because of online card fraud, customers (cardholders) need to pay the entire amount in addition to the high interest rates, reduced benefits and higher fees. Therefore, it is in the best interest of card holders and banks to ensure online credit card faults are somehow eradicated (Chan et al., 1999, p. 67-73).
Key Facts
A survey of UK based online business found that online merchants expect that would around 1.8 percent of their online revenue due to credit card fraud (Brabazon., et al., 2010, p. 1). The identities of the criminal fraudster can range from complex crime syndicates to homemakers, and their victims include individuals, as well many employees working with Fortune 500 companies and the organizations themselves. The most common form of online credit card fraud is theft that can happen through several ways, from the low-tech dumpster to high-tech hacking. Many hackers use CreditMaster and Credit Wizard type programs for generating the 16 digit sequence of credit card from BINs (Bank Identification Numbers). Having access to the credit card numbers allows fraudsters to conduct multiple transitions from online retailers whose security systems are not advanced enough to block sales from sequential credit card numbers.
Addressing the Problem
There are many ways that be used for tackling online credit card fraud and some of them have already been used by several banks and retailers. In 2001, Google proposed that the best way to end credit card fraud is through developing intelligent cards that includes a keypad, processor and a power source for running the intelligent card (Google Patents, 2001). Other ways include using AIS (Artificial Immune Systems) that can be used in the detecting fraud as AIS helps in flagging non-standard transactions (Brabazon et al, 2010, p.1). CVV numbers are another measure used for addressing credit card default as each card has its own 3 digit number and each online transaction needs the CVV number (Burns & Stanley, 2002, p. 11). According to the rational choice theory of criminology, people’s actions are acts of self-interest and they make decisions for committing crime after they weigh potential risks against the rewards (Bar-Gill & Bubb, 2012, p. 967-1018). Applying the rational choice theory to addressing online credit card fraud would mean making it costlier, tougher, riskier, and technologically inconvenient for hackers to increase the risk of fraud and make it above rewards associated with it.
Tentative Outcomes
There are many concerns with the increasing online credit card default, especially with the increasing number and frequency of online transactions and growth of e-commerce. Solutions such as AIS, CVV number, intelligent cards, etc. are effective solutions for tackling issues related online credit card default. Overall, the outcome of applying these solutions would help online retailers, credit card holders, and banks reduce fraud transactions that have a negative impact on their finances and business.
References
Bar-Gill, O., & Bubb, R. (2012). Credit Card Pricing: The CARD Act and Beyond. Cornell Law Review, 97, 967-1018. doi:10.2139/ssrn.1985948
Brabazon., A, Cahill., J, Keenan., P & Walsh., D. (July 2007). Identifying online credit card fraud using artificial immune systems. Retrieved 20 January 2016 from, http://researchrepository.ucd.ie/bitstream/handle/10197/2736/CEC_2010_AISOnlineCreditCardFraud.pdf
Brody, R. G., Brown, D. M., Chettry, A., & White, W. I. (2014). Proliferation of Credit Card Fraud with Current Technological Advances. Insights to a Changing World Journal, 2014(2), 92-107.
Burns, P., & Stanley, A. (2002). Fraud Management in the Credit Card Industry. SSRN Electronic Journal, 2-16. doi:10.2139/ssrn.927784
Chan, P., Fan, W., Prodromidis, A., & Stolfo, S. (1999). Distributed data mining in credit card fraud detection. IEEE Intell. Syst, 14(6), 67-74. doi:10.1109/5254.809570
Google Patents. (2001). Method and apparatus for minimizing credit card fraud. Retrieved 20 January 2016 from, https://www.google.com/patents/US6188309
