AI Fundamentals for Banking Infrastructure
A Two-Week Primer with Layman Terms and Java Examples
Week 1 – Core Concepts
DAY 1 – DEEP LEARNING Deep Learning is a type of AI that mimics how the human brain learns. Instead of writing rules like “if transaction > £10,000, flag it,” you feed the model thousands of examples and let it figure out what fraud looks like. It uses neural networks—layers of interconnected nodes that learn patterns from data.
In banking, Deep Learning is great for detecting fraud, predicting loan defaults, or analyzing customer behavior. It works best with large datasets and unstructured data like text or images.
Java Example Imagine a fraud detection model
double[] transaction = {1200, 3, 0}; // amount, location code, merchant type
NeuralNet fraudDetector = new NeuralNet();
boolean isFraud = fraudDetector.predict(transaction);
