Minimize your costs and reduce friction by exempting authorisation or authentication requests from SCA & 3DS2 whenever possible.
All the sensitive data is hashed which makes it impossible to go back to the end-user
Privacy was integrated in the architecture of our IT systems and business practices
Our approach is based on preemptive measures rather than remedial ones
By including strong privacy defaults, we keep the interests of the end-user safe
From start to finish, our strong security measures ensure a full lifecycle protection of end-user’s data
We make sure the access to sensitive information is severely controlled
Enygma analyzes historical data, provides transaction monitoring and risk scores events to prevent fraud and suspicious behavior
Enygma’s advanced self-learning models provide a holistic view of customers and identify at-risk activity to reduce chargebacks and false positives
Enygma’s fully adaptive machine learning models will ultimately safeguard transactions, provide advanced, explainable anomaly detection and increase acceptance rates thanks to its intelligence-led solutions
Enygma delivers risk intelligence in less than 300 milliseconds
Detect financial crime with transactional monitoring and improve your risk management worldwide
Reduce chargebacks by 87% and false positive alerts by 95%
Monitor across any type of product or channel to maximize business growth
Enrich the predictive server and improve the results with machine learning in real time
Reduce your cost by choosing whether to activate 3D Security or not when needed
Integrate Enygma with a variety of third-party enterprise systems in just a few hours
No matter who we work with, we are ready to take on any challenge
Extract data in a wide array of formats to integrate with your already existing reporting software as well as business intelligence tools
Enrich the predictive server and improve the results with machine learning in real time
Monitor across any type of product or channel to maximize business growth
Reduce chargebacks by 50% and false positive alerts by 95%
The previous spending patterns of the individual payment service user
The location of the end-user and of the merchant at the time of the payment transaction in cases where the access device or the software is provided by the payment service provider
The payment transaction history of each of the payment service provider's payment service users
The identification of abnormal payment patterns of the payment service user in relation to the user's payment transaction history