Entersekt Announces Its Partnership With Capitec Bank To Boost Security For E-commerce Transactions
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Entersekt Announces Its Partnership With Capitec Bank To Boost Security For E-commerce Transactions

Entersekt Announces Its Partnership With Capitec Bank To Boost Security For E-commerce Transactions. Global leader in device identity and authentication solutions, Entersekt announced that it has partnered with Capitec Bank and the bank has implemented its innovative EMV 3D Secure solution that boosts the security of e-commerce payments, while reducing friction for cardholders.

Entersekt integrates NuData Security’s behavioral analytics intelligence into its EMV 3D Secure solution to provide Capitec customers with real-time risk-based authentication for online purchases. “E-commerce or ‘card-not-present’ fraud remains unacceptably high in South Africa, accounting for 80 percent of credit card and 53 percent of debit card fraud according to SABRIC,” Schalk Nolte, CEO of Entersekt said in a statement, “Entersekt’s EMV 3D Secure solution combines our strong authentication technology with the latest in behavioral technology to address exactly this security issue. Our solution is unique in that it is fully customizable, enabling Capitec to create differentiated e-commerce experiences for their cardholders. This implementation is another milestone on our innovation journey with Capitec as we keep pushing the boundaries of digital security and user experience.”

Entersekt was born with bright ideas and big dreams of solving the problem of fraud consumers have to deal with on a daily basis. Over time, a secure, simple, and user-friendly experience became increasingly important. By implementing Entersekt’s EMV 3D Secure solution, Capitec can now identify high-risk e-commerce interactions in real-time, significantly boosting security without impacting the customer experience. The solution is available as a single platform and comes pre-integrated with NuDetect, NuData Security’s flagship product.

It combines behavioral biometrics, machine learning, and insights from billions of anonymous data points to distinguish between authentic users and potential fraudsters based on their online, mobile app, and smartphone interactions, flagging those that represent the highest risk.

By Thomas Chiothamisi
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