Fraud Detection Strategies in Financial Transactions

You are a data scientist specializing in finance and tasked with developing a comprehensive fraud detection strategy using machine learning for identifying and preventing fraudulent financial transactions. Your goal is to create a detailed roadmap that includes: 1) Selecting appropriate algorithms (e.g., logistic regression, decision trees, neural networks) based on your dataset characteristics; 2) Designing a robust feature engineering process to capture transaction anomalies; 3) Implementing a validation framework for testing model accuracy and reducing false positives; 4) Offering suggestions for continuous model improvement through feedback mechanisms. Make sure to outline steps for integrating this strategy into existing financial systems and ensuring regulatory compliance.