CA Technologies has released the latest version of its authentication technologies for the payment industry to help card issues combat fraud, increase revenue and gain control of their fraud detection system.
The latest version of CA Risk Analytics features behavioral neural network authentication models for assessing risk of online, card-not-present (CNP) transactions. The neutral network models are powered by machine learning techniques that capture data about individual user actions and enable CA Risk Analytics to better understand and distinguish legitimate behavior from fraudulent behavior.
“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,” said Revathi Subramanian, senior vice president, Data Science, CA Technologies.
CA Risk Analytics considers both fraud patterns and legitimate transaction behavior and tracks the pivotal players in a transaction: card or device, for example.
Further the solution estimates the risk of fraud using advanced machine learning techniques to understand normal behavior for these pivotal players as well as the fraud risk related to deviation from past behaviors.
The solution benefits organizations as it gives a more accurate assessment of which transaction to authenticate and helps stop fraud in CNP transactions, Subramanian added.
Optimized for 3-D Secure protocol, CA Risk Analytics prevents CNP fraud in 3-D Secure transactions by transparently assessing the risk of a transaction in real time.
CA Risk Analytics is one of the components of CA’s SaaS-based payment authentication solution.
Reports say that over $3.5 trillion is lost each year to fraud and financial crimes associated with several industries. The growing instances of financial fraud also provides a big business opportunity for security solutions providers.
In fact IDC estimated that the market for Financial Crime solutions alone will be nearly $4.7 billion in 2014, with a 5.5 percent CAGR over the 2014-2017 forecast period.
The solution includes intelligent, self-learning authentication technologies that help reduce friction for customers during online checkout and allow card issuers to reduce incidents of fraud, increase revenue and gain unprecedented flexibility and control in their fraud detection systems, CA said.
CA has been focusing on the financial security segment for several years. Today CA Technologies also announced that Hanseatic Bank, a private bank based in Hamburg and operating throughout Germany, has selected CA Transaction Manager and CA Risk Analytics, to prevent fraud and improve cardholder engagement.
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CA Risk Analytics now offers increased flexibility and control for the card issuer. The neutral network authentication models within CA Risk Analytics help reduce fraud with revenue and cost improvements. CA Risk Analytics can now better detect legitimate customer behavior, so there is no need to add friction to the checkout process and challenge the consumer with additional authentication to prove their identity.