Leveraging AI to prevent payment fraud in real time


Leveraging AI to prevent payment fraud in real time

Typical fraud protection

Fraud protection tools generally analyze each online transaction in an attempt to correctly decide which purchases to approve and which to decline. Yet on average, 15% of transactions are difficult to clearly define as either fraudulent or legitimate.

Generally, these 15% of “grey transactions” are manually reviewed, in order to determine whether to accept or decline them. Fraud attractive goods, however, do not allow for a proper manual review process without introducing excessive friction for legitimate buyers.

The result? Either a delayed delivery of e-goods, or a high rejection rate of legitimate customers, both leading to a substantial loss of revenue and a negative customer experience.

What makes nSure unique? understands that digital good fraud is unique, and fighting it requires a different, more accurate approach. These unique challenges led to develop an advanced AI risk engine that leverages deep learning techniques to accurately identify fraudulent transactions. has spent years modeling specific buyer patterns in the field of fraud-attractive goods, learning from millions of digital transactions while constantly adapting its machines to learn from evolving customer behaviors and fraudster attack vectors. Based on its advanced technology and specific expertise, is able to achieve a 98% approval rating on average, with no manual review or delayed delivery of product.

A simple integration process

Implementing is a transparent 3 step process

API Integration
Model Training
Go Live

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