Fraud prevention tactics for financial services onboarding

While fraudulent onboarding is on the rise globally, wise risk management minimizes its effects while improving usability. Reduced user input and increased accuracy lead to better conversion rates while ensuring the seamlessness of the online experience.

Combatting a growing risk

Between 2007 and 2015, fraudulent accounts cost businesses billions of dollars; profit margins decreased by as much as $16 billion yearly, with a large portion of the damage having been caused by new account fraud.

A custom combination between internal initiatives and external reviews of new user data can lead to an appropriate balance between fraud prevention and unchanged usability for customers. The efficiency with which you discern between good and bad applications, as well as define procedures for handling applications that fall into a grey area, can be increased with the appropriate mix of prevention tactics. This may include, but is not limited to, customer identification, device fingerprinting and hot lists of formerly fraudulent users or suspicious activity.

Streamline fraud prevention

While the market for stolen financial credentials keeps growing, the most reliable approach in regards to minimising fraudulent online onboarding is a proactive one. Efficient prevention allows you to detect fraud before it inflicts damage upon your business through services provided to fraudulent users.

Scalable, cost-efficient tactics can be easily integrated into your existing process in order to grant you truly effective data control.Customer identification that incorporates both device fingerprinting and facial recognition adds an extra layer of authentication to the onboarding process, in a way that doesn’t inconvenience the user.

The state-of-the-art facial recognition VisageCloud provides uses deep learning and neural networks to bring 95% accuracy to the fraud prevention game. Coupled with long-term account tracking and monitoring, this proactive approach can make the difference between reactive damage control and combating fraud before the onboarding process is complete.

Here’s how it works for the user – when creating an account with your service, they’re prompted to take one or more selfies and then upload a form of photo ID. Adding several selfies improves accuracy, so the software compares them to each other and to the photo on the ID. Once the user’s identity is confirmed, they can safely proceed with confirming their account. This level of face recognition can bring the same level of trust that’s usually reserved for face-to-face interactions and manual validation of ID cards to online interactions.

Begin improving your onboarding process today.

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