A Primer on Machine Learning Models for Fraud Detection - Simility

One area of machine learning that's getting a lot of buzz in recent years is artificial neural networks (ANNs), aka "deep learning" models, which try to simulate how layers of neurons act together in the brain to make a decision. ANN models are highly versatile and can be used to solve highly complex problems like identifying account takeover using the device's sensor data. While other techniques often require limiting the number of features, multi-layer ANNs can train on thousands of features and scale easily. You may be thinking, "Why not just use deep-learning models all the time?" Training such models requires massive amounts of data (typically, millions of labeled transactions), so deep learning models are really only practical for large companies or those that generate a lot of data points.