Fraud Detection That Accounts for Misclassification Using Cost-Sensitive Logistic Regression

Fraud Detection That Accounts for Misclassification Using Cost-Sensitive Logistic Regression

4 Fraud detection is a cost-sensitive problem, in the sense that falsely flagging a transaction as fraudulent carriesa significantly different financial cost than missing an actual fraudulent transaction. In order to take these costs into account, companies should use a more business-oriented measure such as “Cost,” which allows companies to make decisions that are better aligned to their business objectives. This measure takes into account the actual financial gains and losses incurred in the fraud detection process and is based on the cost matrix [Read More]