Today’s interconnected world has driven online retailing to new heights in importance and prominence, especially in the midst of quarantines. However, continues to be a threat to business owners and customers alike. Worse still, instances of fraud have increased alongside the rise in e-commerce, with no signs of slowing in the immediate future. Understanding what fraud looks like in the age of online retail is critical to protecting yourself from it.
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Upward Trends in 2020
Reports on e-commerce fraud have indicated the increases in cases and resulting losses for years, but coincided with a spike in fraudulent activity. This includes both fraud targeting consumers, such as identity theft and phishing, and fraud that exploits rules regarding chargebacks and credit card payments. Such increases in fraud stem in part from fraudulent actors taking advantage of disruptions to everyday life and changes in shopping patterns—people seek convenience in troubling times, and customers and merchants may neglect proper diligence regarding their digital finances because of other concerns.
Fraud takes many forms in the world of e-commerce, ranging from the simple to the complex. Any of them, though, can seriously harm you if you’re not aware of their existence. Some exploit the process of digital payments, like friendly fraud that uses chargeback requests to claim that products paid for did not arrive. Others are more insidious and technical, —similar to phishing, but it exploits DNS vulnerabilities in browsers instead of relying on tricking users into following false links, making it harder to catch and thwart. Such kinds of fraud need more than simple awareness and education to avoid, requiring up-to-date security.
Working Together Against Fraud
Vigilance is important in fighting fraud, but, much like best practices during a pandemic, this goes beyond protecting oneself only. Automated anti-fraud systems, overwhelmed by new forms of attack, and lock out genuine customers, costing businesses just as much as actual fraud would. Instead, a coordinated using both machine learning and human supervision as part of a broader trust network can help streamline online retailing, recognizing both trusted users and fraudulent activity and sharing this info among merchants.
In this way, businesses and retailers can collaborate with each other and with their customers to better recognize fraud in a more turbulent era of online commerce, benefiting all parties involved.