A Cyberattack is a specific type of cybercrime that involves an intentional attempt by a third party to disrupt or gain unauthorized access to a system or network.
Real-time monitoring: With AI algorithms, organizations can monitor real-time transactions, allowing for immediate detection and response to potential fraud attempts. Increased efficiency: AI algorithms can automate repetitive tasks, such as reviewing transactions or verifying identities, reducing the need for manual intervention.
Explainable AI can help to partly overcome the incorporated risk factors. The term refers to the development of AI systems that can explain their decision-making processes in a way humans can understand. In the context of fraud detection, explainable AI can provide clear and interpretable explanations for why a particular transaction or activity was identified as potentially fraudulent.
Machine learning algorithms analyze vast amounts of data to detect patterns and anomalies, enhancing fraud detection and prevention.