How would you detect a fraudulent transaction in a given geography where users mostly spend online?

Focus on outlining a systematic approach to detecting fraudulent transactions in an online spending context. Start by identifying key data points that could indicate fraud, such as transaction amount, frequency, user behavior patterns, and device information. Discuss the importance of leveraging machine learning algorithms for anomaly detection and how you would train these models using historical transaction data. Consider the geographical context and how local spending habits might influence your detection strategy. Finally, address the need for real-time monitoring and alert systems to respond quickly to potential fraud.