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Gartner stresses fraud detection for mobile commerce |
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By year-end 2013, Gartner says that location information or profile information from mobile phones will be used to validate 90 percent of mobile transactions. The research firm says the rapid adoption of smart phones is forcing banks, social networks and other e-commerce providers to implement the kinds of fraud detection capabilities that have become mainstream with fixed-line computing. "Because of the improving browser experiences on smart phones, mobile commerce and transaction execution are set to increase rapidly," said William Clark, research vice president at Gartner. "We estimate that by the end of 2013, 12.5 percent of all e-commerce transactions will be mobile." Clark said enterprise applications must detect fraud in these mobile environments, but detection tools available today don't work well or at all in the mobile world. He said a number of methods can be implemented to help enterprises detect fraud in the mobile space, but most are still in their nascent stages of development and emerge around 2012 as technically mature systems that work easily and transparently across disparate mobile networks. Avivah Litan, vice president and analyst at Gartner said the evolution of these fraud detection tools will play a part in turning mobile commerce into location- and context-aware commerce by increasing the confidence of businesses, financial institutions and end users. Present day fraud prevention methods for mobile applications, outlined by Gartner, include mobile device identification, location of device, and some risk scoring or rule-based models for mobile applications offered by some online fraud detection vendors. Gartner estimates that 70 percent of the largest 20 global card issuers, who authorize more than 50 percent of all payment card transactions, will gradually adopt mobile context information to help detect fraud on fixed-line transactions, and that by year-end 2015, more than 15 percent of all payment card transactions will be validated using context-aware profile information. |
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