Combatting Transaction Fraud: Strategies, Challenges, and Solutions in the Age of Online Sales Acceleration
Transaction fraud has accelerated in recent years, especially during the pandemic when online sales saw major growth. To combat this increasing risk, acquirers are turning to real-time AI, data-rich fraud monitoring, and various strategies to detect and prevent fraudulent transactions. Finextra’s report, Seeking Approval: Acquirers vs. Transaction Fraud, provides insights from industry experts on the evolving landscape of fraud prevention in the payments industry.
One of the key insights from the report is the need for a combined approach to fraud detection, combining rules-based systems with machine learning and shared global data. As fraudsters become more sophisticated and data-driven, traditional rules-based solutions are no longer sufficient to detect and prevent fraud effectively. Acquirers are turning to advanced AI and adaptive analytics to stay ahead of evolving fraud techniques.
Industry experts interviewed in the report also emphasize the importance of global scoring data with regional insights. While global data can provide valuable context for fraud detection, it is also important to consider regional trends and behaviors to tailor fraud prevention strategies to specific markets. By combining global and regional data, acquirers can create more robust fraud detection models that are effective across different regions.
Additionally, the report highlights the importance of collaboration and data sharing among acquirers and issuing banks to combat fraud effectively. By sharing insights and data, industry players can identify emerging fraud trends and patterns more quickly, enabling more proactive fraud prevention strategies. Collaboration could also lead to the creation of industry-led consortiums for sharing fraud data and insights.
One innovative solution mentioned in the report is Brighterion’s market-ready AI models, which are trained on anonymized and aggregated global transaction data from Mastercard. These AI models can recognize anomalous patterns in real time, making instant decisions to prevent fraudulent transactions. With low latency and high throughput capabilities, Brighterion’s AI models offer a scalable and efficient solution for fraud detection in high-volume transactions.
Overall, acquirers are facing a tall order in combatting sophisticated transaction fraud, but with the right tools and strategies, they can stay ahead of fraudsters and protect their businesses and customers. By leveraging advanced AI, data-rich fraud monitoring, and collaboration with industry peers, acquirers can create more robust fraud prevention strategies that adapt to the rapidly changing landscape of online sales and payment processing.