What are some common fraud detection algorithms?

What are some common fraud detection algorithms?

Common fraud detection algorithms include decision trees, neural networks, and logistic regression.

How does a decision tree work in fraud detection?

A decision tree splits data into branches based on feature values, helping to classify transactions as fraudulent or not.

Are neural networks more effective than traditional methods?

Neural networks can capture complex patterns in data, often outperforming traditional methods in large datasets.

What role does machine learning play in these algorithms?

Machine learning enhances fraud detection by allowing algorithms to learn from data and improve over time.

Can you give examples of real-world applications?

Sure! Banks use these algorithms to monitor transactions, while e-commerce platforms use them to detect payment fraud.