The global e-commerce market continues to grow rapidly, and is predicted to be worth $2.4 trillion by 2019. As a result, the market continues to attract not merely ever-greater levels of fraud, but different and ever-more sophisticated types of fraud, too.
In the 2016 Fraud Report, Worldpay examined Mobile Fraud, the role of Social Media to combat fraud and how properly leveraging internal data assets helps merchants identify fraud.
Meanwhile, the report examines the growth of one of the most current issues in cyber security: awareness of the Internet of Things (IoT) as a risk factor in data breach. It also then examine the growth in the application of Machine Learning techniques in combating fraud and finally covers the satisfying role of the Fraud Professional.
While relatively new threats, such as the vulnerability of data produced by the Internet of Things (IoT), have grown considerably over the past year, the biggest and most concerning issues facing merchants in 2017 were: Friendly Fraud, Clean Fraud and Account Takeover.
Merchants are dealing with these fraud types in different ways. Increasingly, AI and Machine Learning is playing a key role – there has been a significant growth in the deployment of machine learning software during the last year, although no organisation has turned control 100% over to automated controls. Most respondents expect this trend towards automation to continue, in order to stay ahead of fraudsters.
Complex Fraud: the challenge continues to grow
Merchants reported that fraud types such as Friendly Fraud, Clean Fraud and Account Takeover are all increasing. Perceived reasons for this increase vary: Friendly Fraud increases are attributed to an increasing tendency to ‘game the system’. Whereas Account Takeover is driven by professional fraudsters benefiting from the fruits of increased data breaches and more sophisticated phishing attempts. Friendly Fraud was reported as the most prevalent fraud type in 2017.
Internet of Things: a rapidly maturing threat
As the connection of home systems and smart devices becomes more common, data is more vulnerable, and the risk of a personal or business data breach becomes more likely. Because of this, the majority (52%) of businesses enforce a policy of restricting the installation of interconnected devices, and a similar proportion (52%) believe that we have not yet seen a peak in breaches or malicious activity from this source.
Machine Learning: an increasingly powerful tool
Some companies are allowing Machine Learning algorithms to make more decisions, while others are building their own tools. None of our respondents reported turning control 100% over to machine learning. This is because merchants are conscious of the need to strike a balance between automation and human judgement. However, companies are increasingly employing experienced data scientists to analyse their data for a range of applications, including fraud detection.
Fraud Teams: a satisfying role
78% of fraud team professionals find their role highly satisfying. Our research shows that individuals are motivated by the tangible impact they have on their companies’ bottom line but also by the personal satisfaction gained by preventing a fraudster defrauding their company or an innocent cardholder.