Anomaly Detection & Introduction to Fraud Modelling

Anomaly Detection & Introduction to Fraud Modelling is a workshop dedicated to fraud and anomaly detection.

Topics

• Anomalies using statistical techniques like z-scores, robust z-scores, Mahalanobis distances, k-nearest neighbors (k-NN), and local outlier factor (LOF)
• Good features (recency, frequency, and monetary value as well as categorical transformations) for detecting and preventing fraud
• Anomalies using machines learning approaches like isolation forests and classifier adjusted density estimation (CADE)

Who should Attend

• Engineers
• Data Scientists
• Software Engineers
• Analysts