This week, Cathy Ross, president and co-founder of Fraud.net sat down with Bradley Chalupski, editor-in-chief of Merchant Fraud Journal to discuss friendly fraud. One of the more common types of e-commerce fraud, “friendly,” or first-party fraud is when apparent customers make a digital e-commerce purchase and then go back on this promise of purchase. This happens because they either obtained a better deal somewhere else (e.g. a lower price on an online airline ticket), or didn’t end up needing the service (e.g. travel insurance), or just didn’t want to pay for the goods or services they received. According to a Fraud.net survey, friendly fraud now occurs with 50 percent greater frequency than third-party fraud — fraudulent use of a stolen credit card, for example. To sum it up, friendly fraud is a problem that is costing online businesses billions of dollars per year.
In this interview, a segment of Merchant Fraud Journal’s “To Catch a Fraudster” series, Cathy Ross tells riveting stories of the most absurd moments of e-commerce fraud, experienced firsthand at Fraud.net. Additionally, Ross also shares tips for how to protect your own e-commerce business from these attacks.
Listen to the full podcast.
E-commerce Fraud and the Future
To Catch a Fraudster is a podcast for eCommerce merchants and enterprise security professionals who dream of vengeance on the thieves, hackers, and con artists stealing their revenue and customer data. Merchant Fraud Journal interviews the entrepreneurs, fraud experts, and corporate leaders on the front lines of the war against fraud. Learn from the mistakes of others and implement the tactics, strategies, and technologies you need to secure your store or protect your corporate systems from attack.
Fraud.net is a cloud-based fraud detection system, combining data together from different sources in to one view is the key to combating fraud. Fraud.net is more than a product, solution, or set of fraud-prevention technologies. It’s a global, anti-fraud network based on collective intelligence. Fraud.net helps clients detect and prevent fraud for all transactions using all their data, and anonymized data from the network to evaluate financial risk.