Fraud Detection with Advanced Outlier Detection Algorithms
Online fraud costs the global economy more than $400 billion, with more than 800 million personal records stolen in 2013 alone. Increasingly, fraud has diversified to different digital channels, including mobile and online payments, creating new challenges as innovative fraud patterns emerge.
One technique organizations use to detect and prevent electronic fraud is outlier or anomaly detection. In fact, it is the core of one of our fraud protection layers, called DetectTA (the TA stands for transaction anomaly). Through anomaly detection, companies are able to differentiate between normal and abnormal customer account behavior by using statistical analysis. Patterns can be used to identify potentially fraudulent transactions, such as a spending spree on expensive luxury items. If not typical for an account these would be considered outlier transactions, which by definition, deviate from normal behavioral patterns. [Read More]