Mastercard has launched an innovative approach utilizing generative AI and graphical technology to significantly enhance the identification of stolen payment cards, doubling its detection rate and allowing for risk identification before cards are maliciously used. This technology has a profound impact on both online and brick-and-mortar retailers, helping to reduce fraud losses, improve transaction security, and enhance customer experience. By quickly scanning vast amounts of card data and transaction information, the system can identify new fraud patterns, predict and infer partial visible card information, reconstruct complete card details, promptly alerting banks and protecting cardholders against fraud.

Mastercard Inc. joins the generative AI race and has developed its own model to help numerous banks within its network detect fraud. The newly launched AI model, known as 'Decision Intelligence Pro', reportedly increases the fraud transaction detection rate by up to 300% compared to previous models. The model takes into account the cardholder's merchant history to assess whether a transaction aligns with their typical behavior patterns, completing the entire process in approximately 50 milliseconds.

Scientists have successfully developed an AI tool using machine learning techniques that can trace the authenticity of wine. The tool precisely traces back to specific vineyards and wineries through differences in the concentrations of trace compounds. In addition to combating wine fraud, this technology can also monitor the wine production process and improve the quality of winemaking. The application of this tool is expected to reduce the costs of making top-quality wine, benefiting more people.

Artificial intelligence plays a significant role in fraud detection by leveraging its ability to analyze large datasets and identify complex patterns. Machine learning is key to AI in fraud detection as it learns from historical data to detect anomalies. AI can handle vast amounts of both structured and unstructured data, focusing on recognizing anomalies within datasets, which is crucial for fraud detection. AI can create user profiles based on historical data and monitor transactions in real-time, ensuring that fraudulent activities are detected promptly. Reducing false positives is very important as it helps in capturing fraud while ensuring a smooth user experience.