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Monday, 27 October 2014 14:17

CA ups the ante in fraud detection with new release Featured

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CA Technologies has released its next generation Risk Analytics solution which it says will allow card issuers to reduce incidents of fraud and gain ‘unprecedented’ flexibility and control with their fraud detection systems.

CA vice president, solution strategy Asia Pacific & Japan, Vic Mankotia, says this latest version of the risk analytics solution incorporates “sophisticated, patent-pending behavioural neural network authentication models for assessing risk of online, card-not-present (CNP) transactions”.

“There is an increase in market demand for a more advanced CNP fraud detection strategy that goes beyond just comparing the current transaction to established fraud indicators,” Mankotia says.

“CA Risk Analytics considers both fraud patterns and legitimate transaction behaviour and tracks the pivotal players in a transaction, card or device for example.

“It estimates the risk of fraud using advanced machine learning techniques to understand normal behaviour for these pivotal players as well as the fraud risk related to deviation from past behaviours. This results in a more accurate assessment of which transaction to authenticate and helps stop fraud in CNP transactions.”

According to Mankotia, history shows that the continued global rollout of the EMV standard and the increasing distribution of Chip and PIN cards will result in an increase of CNP fraud attempts.

“Card issuers and merchants want a solution that improves fraud detection without increasing cardholder friction. CA Risk Analytics and its behavioural neural network models will result in ‘zero touch’ authentication that will instill a level of confidence and streamline the online checkout process.”

Key features and capabilities added to the latest version of CA’s Risk Analytics solution are:

•    Increased flexibility and control for the card issuer. Card issuers can instantly change score thresholds and policies at their discretion. This gives them more control over their business so they can adapt to market conditions, better handle staff fluctuations or deal with current events that may demand examining a higher or lower volume of transactions while still ranking the most risky first. Card issuers no longer have to rely on vendor-only control of their system settings

•    Reduced fraud with revenue and cost improvements. The neural network authentication models within CA Risk Analytics help improve the accuracy of detecting legitimate from fraudulent transactions. This helps to reduce fraud and increase revenue. Better accuracy in detection also helps manage the cost of transaction analysis

•    Better customer experience. Because the models in CA Risk Analytics can better detect legitimate customer behaviour, there is no need to add friction to the checkout process and challenge the consumer with additional authentication to prove their identity.

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Peter Dinham

Peter Dinham is a co-founder of iTWire and a 35-year veteran journalist and corporate communications consultant. He has worked as a journalist in all forms of media – newspapers/magazines, radio, television, press agency and now, online – including with the Canberra Times, The Examiner (Tasmania), the ABC and AAP-Reuters. As a freelance journalist he also had articles published in Australian and overseas magazines. He worked in the corporate communications/public relations sector, in-house with an airline, and as a senior executive in Australia of the world’s largest communications consultancy, Burson-Marsteller. He also ran his own communications consultancy and was a co-founder in Australia of the global photographic agency, the Image Bank (now Getty Images).

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