Guarding the Global Village: Tackling the Fraud Threat in Online Marketplaces
Many online marketplaces and shopping sites are taking the digital world by storm with user-friendly platforms for buyers and sellers to exchange goods and services. According to analyst Forrester, half of all online spending came via marketplaces in 2016, a figure set to rise to 66% by 2022.1 However, the success of these platforms is crucially predicated on trust: without it, the whole business model comes tumbling down. That’s why the growing prevalence of online fraud and continued flow of breached identity data onto the dark web are serious causes for concern.
To respond effectively, online marketplace operators need advanced machine learning-powered tools to gain a holistic view of each customer interaction. Doing so will not only help them to better detect and block fraud, but also help drive trust in their platforms while improving the customer experience.
A global, digital village
Over the past few years, online marketplaces have helped to reinvent e-commerce with a model benefitting buyer and seller alike. Time-poor consumers get maximum choice for minimum effort, while sellers gain an opportunity to reach a much larger pool of potential customers than they would by operating from a single digital store front. It’s no coincidence that some revenue estimates for global marketplace providers are expected to more than double.
Online marketplaces represent a village economy model updated for the digital age. They act as brokers of trust, nurturing a community of buyers and sellers, with buyer feedback helping to maintain transparency and assurance. The problem, for online marketplace providers and the businesses selling on their platforms, is that fraudsters are increasingly looking to undermine this all-important trust.
Fraud hits home
These scammers are taking advantage of the global nature of online marketplaces, the anonymity of the internet and ready availability of breached identity data to impersonate shoppers and pose as businesses. Key fraud types on these platforms include:
- Identity fraud: Fraudsters use stolen or synthetic identity data to open accounts, often to sell counterfeit goods.
- Payment fraud: Fraudsters use stolen payment data to make unauthorized purchases.
- Fake listings/profiles: These are intended to trick users into making payment for non-existent items.
- Account takeover (ATO): Hijacking of existing users’ accounts, which can be particularly difficult to spot.
Online fraud impacts the online marketplace ecosystem in multiple ways. Apart from the direct financial hit from fraud and the extra operational costs it incurs, there’s the knock-on impact of reputational damage and lost trust which can lead to customer attrition. This can further impact the affected business financially, as consumers choose to shop elsewhere online.
Time for action
Online marketplace providers need an effective response to rising fraud levels that provides improved insight and analytics to drive faster, more accurate decisions and competitive advantage. In practice, this means seeking out advanced fraud prevention platforms that combine large volumes of disparate in-house and third-party data and then apply machine learning algorithms to make sense of it. The power of machine learning is to identify patterns of suspicious behavior that human eyes may miss, while proactively tuning key rules and filters to remain cutting edge even as fraud evolves.
Simility’s Adaptive Decisioning Platform empowers fraud teams at some of the world’s largest online marketplaces. Its highly effective, automated approach detects and blocks fraud in real time. This not only reduces the costs associated with high levels of false positives, manual reviews, and chargebacks but works to preserve trust and reduce friction for legitimate users.
As fraud continues to grow and tactics become more sophisticated, next-gen tools like this will become a vital differentiator for the platforms that increasingly dominate digital commerce.
1 Forrester, “Half Of Online Retail Spending Came From Marketplaces In 2016,” https://go.forrester.com/blogs/half-of-online-retail-spending-came-from-marketplaces-in-2016/