Anomaly Detection is the technique of identifying rare events or observations which can raise suspicions by being statistically different from the rest of the observations. Such “anomalous” behavior typically translates to some kind of a problem like credit card fraud, a failing machine, or a cyber attack. In finance, with thousands or millions of transactions to watch, anomaly detection can help point out where an error is occurring, enhancing root cause analysis and quickly getting support on the issue. Anomaly detection helps the monitoring cause of chaos engineering by detecting outliers and informing the responsible parties to act. Machine Learning and AI are increasingly being used for anomaly detection for fraud detection and Anti-Money Laundering (AML).