Anti-fraud solutions have platform appeal

MANGOPAY’s acquisition of Nethone highlights the value of anti-fraud solutions to online marketplaces. The trend can be seen at Paypal too.
30 November 2022

Customer security champions: Romain Mazeries CEO of MANGOPAY and Hubert Rachwalski von Rejchwald, CEO and Co-founder at Nethone. Image credit: MANGOPAY.

Digital payments solutions are great for customers. Frictionless payments speed up the process for merchants and shoppers. But they are not necessarily the only ones paying attention. Bad actors will be taking an interest too. As the saying goes, ‘where there’s money, there’s crime’. However, companies certainly don’t have to make it easy for adversaries. On the contrary, payments providers – which include up-and-coming fintechs as well as long-established firms – have a suite of anti-fraud solutions to choose from.

This month, MANGOPAY announced that it had acquired Nethone – a machine learning-based fraud prevention SaaS company – deepening the anti-fraud solutions layer within its payments infrastructure. MANGOPAY, formed in 2013, provides programmable e-wallet solutions for crowdfunding and B2B platforms, as well as marketplaces and e-retailers hosting third-party vendors. And the firm is well aware that continued success depends on delivering excellent customer service and user experience.

This points to one of the challenges in providing effective anti-fraud solutions. Products need to get their decisions right. False positives will annoy legitimate customers who find their payments being blocked unnecessarily. And, on the other side of the coin, clients who have funds stolen or misused won’t be happy either. Fortunately, artificial intelligence (AI) and related tools are proving to be very useful in this area.

Paypal has been using machine learning since the 1990s to sniff out suspicious behavior on its payments network. As soon as digital payments took off, they quickly noticed that fraud levels were rising too and wasted no time in leveraging one of their biggest assets – big data. Typically, the more information that you can use to train AI algorithms, the better they perform – even more so with the latest deep-learning techniques.

Big data boost

Any guesses on the number of transactions that Paypal processes each year on customer and merchant sides of its business? The answer is more than 15 billion, which adds up to a huge amount of intelligence. What’s more, real-time data modeling has the power to highlight shifting fraud patterns. As bad actors attempt to obfuscate their actions, AI is already there sounding the alarm.

The payments giant encourages merchants to be proactive by using anti-fraud solutions enabled by big data and has clear evidence that its tools work. Also, it’s not just about saving money. Adaptive risk management approaches save time too, by reducing the number of transactions that must be reviewed manually. In Paypal’s case, existing account holders don’t even have to worry about integration as the anti-fraud solutions are ready and waiting.

Rich data can build a very useful defense against fraudsters. With more than 20 years of Fintech experience, Paypal can tap into the collective wisdom of 330 million active customers and 25 million merchants to benchmark legitimate versus suspicious behavior. MANGOPAY, which is approaching a decade of fintech operations, benefits from information assets too.

“Every platform must have a deep understanding of its users in real time throughout their entire customer journey to reduce fraudulent activity,” comments Romain Mazeries, CEO of MANGOPAY. The ramping up of data intelligence is a clear trend as payments have become increasingly digitized. And authentication protocols such as 3d Secure 2 (3DS2) have shown that improved fraud detection doesn’t have to turn into a pain point.

In fact, studies show that 3DS2 – which interrogates 40x more data than 3DS1, its predecessor – generates more sales with less friction. Efficient fraud detection systems that don’t impact user experience lead to fewer potential purchases being abandoned in online shopping carts. And these anti-fraud solutions need to be implemented throughout. Bad actors are canny at picking low-hanging fruit.

E-commerce support

Research suggests that third-party sellers could capture 59% of global e-commerce sales by 2027, which emphasizes why digital marketplaces are strengthening their defenses. Returning to the news that MANGOPAY and Nethone have joined forces, the announcement highlights such moves. And, naturally, anti-fraud solutions capabilities need to be omnichannel – protecting customers no matter how they choose to shop.

Being able to gather intelligence across different channels can give financial service providers the ability to discover more sophisticated fraud rings and help to shut down a potentially greater number of enterprise vulnerabilities. Also, another win is being able to package anti-fraud solutions together efficiently, streamlining the tech stack.

Having to power up multiple tools from different vendors complicates the workflow for security teams and risks that vital clues are missed. Ideally, headline data should be easy to collate and reports straightforward to generate to enable efficient auditing.

To recap, the rewards for getting things right are fewer checkout abandonment issues for merchants thanks to truly frictionless payments. And, by relying on AI algorithms capable of recognizing rogue behavior, users can be confident that when transactions are revoked, it’s for the right reasons.