We are about to enter the most wonderful time of the year. As consumers increasingly turn towards online and mobile commerce, are you confident in your card-not-present fraud detection capabilities?
2020 has been a year of great surprise and change. While the global health pandemic has changed how we physically interact with each other, it has also revolutionized how we shop. This year, retailers have seen e-commerce sales surpass all projections as consumers continue to uphold personal safety and social distancing guidelines. In fact, Deloitte projects that retailers can expect a surge in e-commerce sales by 25-35% this holiday season – generating up to $196 billion.
But as consumers increasingly turn towards online and mobile commerce, many fraud and security teams are struggling to protect against card-not-present fraud. Case in point, Juniper Research has projected that retailers will lose around $130 billion in card-not-present (CNP) fraud between 2018 and 2023.
So how do you make sure mobile and online payment channels are secure against card-not-present attacks – such as account takeovers, malware, chargebacks and botnet attacks? This is where a hybrid approach featuring a combination of rules-based alerts, event monitoring, transaction risk scoring and actionable machine learning models becomes essential. By combining these features with a continuous feed of transaction data and channel intelligence, retailers and card-issuing banks can make preemptive decisions around card-not-present fraud without the risk of increased false positives and unnecessary customer service disruption. Existing card-not-present fraud defences are strengthened through the ability to:
- Screen every transaction field in the message payload — to detect suspicious fields and respond to anomalous transaction activity in milliseconds.
- Incorporate real-time machine learning that utilizes more detailed transaction data feature sets — to predict and adapt to existing and new fraud patterns that are emerging in the card-not-present fraud space
- Feed risk scoring engines with a much broader data set — to increase the precision of transaction scoring and become more accurate at blocking and preventing card-not-present fraud transactions
In summary, we would really like to help you make this the year you can rest easy, and get a real holiday thanks to card-not-present fraud for your financial institutions. For more tips on how to gain peace of mind that every card-not-present transaction will complete reliably and securely, read about INETCO Insight for Payment Fraud Detection or request a demo.