Preventing Online Payments Fraud with ML: Covery at MRC London 2019
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Preventing Online Payments Fraud with ML: Covery at MRC London 2019

Preventing Online Payments Fraud with ML: Covery at MRC London 2019

MRC London definitely causes a stir among hundreds of online merchants, vendors, and e-commerce brands this year.

On May 13–15, the Royal Lancaster Hotel, where the event is held, expects 750+ like-minded professionals in fraud, data science, and e-commerce from more than 30 countries to discuss the best practices and rising opportunities in payments and fraud prevention.

Covery team, presenting a global risk and fraud management platform, will share expertise on how to make the best use of ML in payments security and fraud detection.
Especially, Covery is going to share ideas about how e-commerce business can be enhanced with the help of right risk assessment, device fingerprinting, and KYC procedure automation.

“The more companies emerge in e-commerce, the more fraud we face. However, while deceit schemes forge ahead, anti-fraud companies are not standing still and use advanced technologies, like Machine Learning, to end fraud,” says Pavel Gnatenko, Covery’s Product Owner.

“When it comes to fighting online payment fraud typical for e-commerce, several advantages of applying ML become evident. Here I’d like to name the real-time decision-making, improved accuracy of fraud detection and classification, and rapid response to real-world changes.

We are looking forward to sharing more insights gathered by Covery platform during the implementation of ML into e-commerce products fraud prevention with MRC London attendees” added Pavel.

If you are interested in learning how Covery can support your business, we welcome you to reach us out and arrange a meeting by emailing

About Covery

Covery is a global risk management platform helping online companies solve fraud and minimize risk. Covery focuses on the versatility of the product and its adaptability to each type of business, based on the individual characteristics and customer needs using both rule-based and machine learning approaches. The company works with high-risk as well as with low-risk industries offering customized solutions for every customer. Find out more at