The international fraud rate attack on banking institutions was two times higher in 2017 than it was in 2015.

Banks and financial institutions are a prime target. In today’s fast-paced digital landscape, a frictionless customer experience is a must. It also enlarges the playing field for fraudsters. So how do you increase fraud prediction without damaging the onboarding or transaction process? By integrating SEON into your platform, you get a complete solution for real-time, transparent and efficient fraud detection without false positives - whether it is to detect payment fraud or account takeover.

Onboard new clients safely

Through device fingerprinting, email validity, IP analysis or social media profiling, SEON gives you all the tools to mitigate risks for new account openings. The system detects anomalies based on data of your choice, so you get a complete picture of who you are letting into your user base.

Comply with regulations

SEON helps banks comply to PSD2, RTS and GDPR regulations for data collection. Payments up to 500€ can be monitored by the transactional risk scoring system according to RTS regulation, so SEON’s fraud detection engine fits seamlessly into that new value chain.

Protect existing customers

SEON’s real-time prevention tools detect anomalies so you can immediately act when something isn’t right. Whether to prevent the use of stolen credit card credentials or account takeovers, your customers’ safety is not only protected, but increased.

Recover lost fraud revenue

SEON’s management tools takes all of the relevant risk vectors into consideration to reduce chargeback rates and friendly fraud. No need to go into complicated disputes when you have all the fraud prevention facts at hand.

Maintain outstanding UX

Transaction or authentification analysis comes with zero effect on user experience. SEON enables dynamic 2FA to improve the UX and minimise costs. Decision making happens in real time, in the blink of an eye.

And the best of all?

A fraud prevention system that improves with every use.

The SEON engine fine-tunes its algorithm thanks to machine-learning and human intelligence. Blacklist databases are constantly updated across the network of SEON clients, so fraud prediction results get increasingly accurate overtime.

The Downsides of Shared Blacklists

In the market for a fraud prevention tool? You’ll look at various options. Compare providers. And you’ll soon notice most of them proudly offer shared blacklists as a strong selling point. The problem? It’s not always something you want.

A Deeper Look at Gambling Fraud: Tackling Promo Abuse

We previously wrote about the basics of gambling fraud. Today, we’ll look ar a particularly prevalent form of abuse: when promos are used to cheat against gambling platforms.

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As developers of a fraud prevention tool, we have to know what we’re up against. It’s not enough to create a platform that reduces fraud by detecting patterns: we have to understand exactly how fraudsters operate.