Our solution can stop account takeover fraud in its tracks at the login attempt and provide human-readable explanations of the ML models’ reasoning to your team.
We leverage raw behavioural data (keystrokes, mouse movements, gyroscope, touchscreen, etc.) to detect anomalous behaviour while a user logs into a registered or new account.
From the very first login attempts, we detect any suspicious activity that indicates the likelihood of ATO fraud. Where social engineering scams may have worked with unsuspecting customers, leading to a compromised account, our machine learning models never fail to detect the slightest deviation from regular customer behaviours.
Our silent alarm picks up on the slightest hint of ATO attacks by spotting non-obvious correlations and patterns in user behaviour and device setup. Behavioural biometrics and digital fingerprinting make this possible while ensuring a frictionless user experience, completely invisible to regular customers.
Every customer has different requirements. We can help you implement the best possible fraud prevention based on our fraud intelligence and bespoke machine learning models trained to detect account takeovers.
Technology must be at the forefront of precise fraud detection. We've created a product that will not only provide the best fraud detection but it's also super user-friendly for you and/or your fraud team.
At the forefront of our fraud prevention solution stands in-depth user profiling. We create a complete customer profile by obtaining 5,000+ attributes about each user, including behavioural, device, and network data. We go beyond data made available by the user by digging deep into your customers' sessions to discover fraudsters, bots and dishonest users.
Our machine learning models analyze those data to spot non-obvious patterns and behaviours to detect fraudsters and automate decision-making faster than heuristics and manual rules sets, with fewer false positives. The process of gathering data and analysis happens in real-time, and in less than one second you block fake users who try to commit fraud.
What you get is an actionable refuse/review/accept recommendation for your risk management team. We also deliver a human-readable explanation of the ML results in one place — the Nethone Panel, so you understand why the decision was made and review it manually if necessary. You can also fully customise your decision logic to fit your needs.