Offer your customers secure and seamless digital transactions with Wibmo’s Risk-Based Authentication (RBA) framework.
In today’s modern world of rapidly evolving business dynamics, customers want a seamless and instant experience at every transaction, be it for ordering food online or making reservations for the next blockbuster. In situations such as these, where time is of key essence, the onus is on you to validate the authenticity of the customer and actively protect your business from fraudsters who are getting better at manipulating data.
To meet the challenges of today and tomorrow, you need access to an intelligent risk based authentication system which can leverage data insights for real time decision making and provide your customers with a frictionless transaction experience.
Wibmo’s proprietary ACCOSA RBA framework provides you with the ability to analyze data from various customer touchpoints in real-time, calculate risk from every individual transaction and automatically arrive at a decision of either increasing or decreasing the need for additional authentication.
Try out Wibmo’s Risk-Based Authentication framework today and provide your customers a hassle free and secure digital payment experience across devices.
To know more, download our brochure.
Active Analysis for Real-Time Decision Making
Designed on Trident FRM, Wibmo’s proprietary fraud detection and prevention engine, our ACCOSA Risk-Based Authentication framework equips your business with the ability to actively gather data from multiple customer touchpoints, analyze and score every transaction in real-time, enabling seamless and quick risk-based decision making.
With the ability to score every transaction, and support for multiple out of band (OOB) authentication points, you have the ability to truly optimize your customer experience.
Wibmo’s Risk-Based Authentication (RBA) framework collects data from the following customer touchpoints.
- Customer transaction activity
- Device fingerprinting
- Location Analytics
- Behavioural Biometrics
- Link Analysis