Trends in the fraud and payments space for 2023

Christian Mangold, the CEO of Fraugster, a payment intelligence company serving the ecommerce and payments ecosystem, shares what should retailers watch out for in terms of fraud in 2023 and get ready

Ecommerce losses to online payment fraud have significantly increased over the past year and were estimated to be at USD 41 billion globally, in 2022. The figure is expected to grow further to USD 48 billion in 2023 and keep increasing by 131% from 2022 to 2027. An increase in interconnected smart devices and online activity has significantly contributed to this trend by making customers more vulnerable.

Increasing fraud not only affects prospective revenues for merchants but also causes harm to their brand and customer loyalty. In an increasingly competitive digital environment, it is not only important for merchants to look out and be aware of new fraud trends in the coming year, 2023, but also to be adequately prepared to fight against it and provide a seamless and safe experience to their customers.

Omni channel methods such as BOPIS (Buy Online Pickup in Store) are set to reach over USD 700 billion in spending over the next five years. As customers are likely to purchase more items when visiting a physical store to pick up their online orders, such business models have proved to be lucrative for merchants.

Merchants adopting omnichannel strategies however need to appreciate that additional comfort to customers comes at the cost of a broader attack surface for fraudsters to exploit. The situation is made trickier as verifying users’ identities becomes difficult due to the lack of information on physical addresses.

In such a scenario, merchants need to gain a more holistic view of the customer. This can be achieved by blending server-side data with account and payment data from fraud systems.

There is a further need for merchants to amend their fraud prevention strategies and gain a holistic view of both customer level and transactional attributes while assessing riskiness. This can be achieved by leveraging advanced technologies like data enrichment, AI, and linking analysis.

Recessionary environments pose a tricky challenge, as people have less money to spend but still want to maintain the lifestyle, they are accustomed to. Friendly fraud attempts have been seen to increase sharply in past economic downturns, costing merchants close to 2x the transaction amount. A 21% uptick was further seen in friendly fraud in 2021, when compared to 2020 levels, given COVID-19. Sectors with high Average Order Value (AOV) such as travel and fashion were the worst hit.

Fraugster’s data further demonstrated a unique trend of an uptick in ‘angry chargebacks’, (defined as chargebacks filed by customers when the merchant is unwilling to offer a refund or provides substandard customer support), increasing from a pre-pandemic baseline of 15% to over 50%. Merchants should be prepared for a rise in such evolving patterns of friendly fraud in response to inflationary pressure.

Apart from investing in challenging chargebacks that have a high probability of winning, merchants can be a step ahead by focusing on root causes and taking necessary actions to prevent them. Some best practices include:

a. Quick and easy resolution of consumer issues:  this can be achieved by providing clear and direct channels for customers to resolve issues and offering seamless order and shipment tracking services.

b. Accurate merchant and billing descriptors: improving transaction descriptors that cardholders see on their statements and providing smart terms and conditions concerning returns and refunds, aid in achieving this goal.

Social engineering attacks, where users are tricked into giving away their personal information while the fraudster poses as an authority figure, have become advanced and can be done at scale. The rise in such attacks has been driven by easily accessible software for building deep fakes and changing voices, along with more decentralised, privacy-focused messaging apps where consumer contact information can be easily bought and sold.

The darknet further has long acted as a haven for fraudsters looking to build a fake identity by buying cheaply available customer PII (Personally Identifiable Information), credit card, passports, and other documents for as low as USD 20. Fraudsters are now taking it a step further by selling device fingerprints on it.

These are gained via bots controlling machines infected by malware. The purchase of a device fingerprint gives fraudsters access to a user’s passwords, usernames, browser cookies, and IP addresses. It is hence key for merchants to not just depend on device ID as a sole identifier but combine it with advanced AI and data enrichment to accurately assess risk.

It will become increasingly complex to tell apart genuine shoppers from bots and fraudsters, especially as fraudsters are becoming more sophisticated at mimicking the behaviour of good users to avoid detection. On the one hand, this could increase the percentage of false positives, on the other hand, it will test how accurately vendor solutions can distinguish good transactions from bad ones without inducing additional customer friction. Striking the right balance between increased security and friction for customers makes this even more complex.

This calls for merchants to leverage advanced technologies like device intelligence, data enrichment, and network intelligence, powered by Machine Learning to assess customer risk. Such advanced technologies allow for basic data points such as customer name, email address, payment information, phone number, etc to be enriched and gain insight into customer-level attributes such as location, transaction history across merchant data networks, device type, and age, card type, etc. The detailed customer and transaction level attributes allow merchants to assess risk more accurately, without inducing unwanted friction.

Merchants also need to prepare against fraudsters ready to exploit the openness of web3. The rise of web3 and the metaverse would not only trigger increased purchases of high-value digital assets like NFTs but also low-value, high-frequency, in-game purchases like swords, skins, and usernames. These environments can thus be preferred locations for fraudsters testing stolen financial instruments before going on to make higher-value purchases. This in turn presents a massive chargeback risk for merchants, and especially gaming companies.

In this light, it is important to address scaling and security issues for companies involved in this space. There is also a need to develop proper KYC procedures to verify users’ identities across different blockchains. Complying with AML and compliance standards also remains to be a space for development.

Post the positive impact of PSD2, a new directive, PSD3 is set to come into effect in the next few years. It is key for merchants in the EU to be aware of such developments and make prior preparations to avoid sudden shocks.

Recent discussions and recommendations on PSD3 have been focused on areas of Strong Customer Authentication (SCA) and improved Open Banking standards. The extension of the SCA period from 90 to 180 days has been one of the key topics in discussion, expected to positively impact merchants by reducing customer churn. Emerging areas like cryptocurrencies, BNPL, or other forms of alternate payment methods must be prepared for increased regulations.

The onset of the 6th Anti-Money Laundering Directorate (6AMLD) has further broadened the scope of money laundering offenses, to include persons aiding, abetting, and inciting relevant offenses. Merchants thus need to not just think that AML regulations only affect the ‘poster children'; including Pandora Papers or an eclectic mix of politicians, rockstars, and dictators - but also their daily activities. There should be an increased focus on transaction monitoring, installing rigorous KYC and KYB checks, and screening each transaction through sanction and PEP lists.

One-click checkouts and shorter signups have made commerce frictionless but led to an increased risk of fraud which could negatively impact both customers and merchants. To be better prepared to fight against such emerging fraud patterns, merchants need to have a robust fraud prevention system in place.

Fraugster solves these challenges with a scalable solution that leverages advanced machine learning and AI to give a 360-degree view of the customer and transaction in just 15 milliseconds. Advanced data enrichment and smart - ecommerce specific linking, enable merchants to uncover even the most sophisticated fraud. Whitebox AI further enables analysts to understand the key factors influencing risk scores and customize rules seamlessly for better accuracy and lower false positives.

About Christian Mangold

CEO Fraugster

Christian is a seasoned growth executive who successfully scaled SOFORT before its acquisition by Klarna, where he served as Managing Director for the DACH region. As CEO he leads Fraugster’s entire day-to-day operations. In his spare time, he is an outdoorsman who likes to ski and sail with his wife and three children.

About Fraugster

Fraugster is a payments intelligence company that helps the ecommerce ecosystem to minimise fraud and maximise revenue by making smarter real-time business decisions. We help our customers (PSPs, BNPL providers, and online merchants) solve multiple use cases by giving them access to various, interoperable products via one integration. Fraugster has developed one of the most accurate AI fraud prevention solutions on the market and is backed by some of Europe’s most reputable deeptech investors.