Description
To effectively perform real-time assessment on these aspects, many companies use the latest technological applications. Fraud detection systems use real-time transaction risk scoring algorithms to identify questionable purchases or payments. These systems consider transaction details, user profiles, behavioral biometrics, geolocation, IP/device metadata, account information, and more.
The advancement of artificial intelligence and machine learning are also aspects that have advanced our ability to perform real-time risk assessments. We discuss these concepts and how they are used. This course focuses on step one and two when performing a real-time fraud risk assessment. Those steps include:
- Step One – Planning
- Step Two – Identifying Risk
Future courses will cover the remaining steps in the process.
This course is a continuation in our series on Fraud Trends for the Future. Within this course we discuss the importance of performing a real-time risk assessment. We also discuss the many variables that are involved in this process and how they should be considered. Other courses in the series include:
˃˃ Fraud Trends for the Future – Automation and Machine Learning
˃˃ Fraud Trends for the Future – Examining Account Takeovers
˃˃ Fraud Trends for the Future – Targeted Attacks
˃˃ Fraud Trends for the Future – Understanding Synthetic Identities
˃˃ Fraud Trends for the Future – Mitigating Synthetic Identities
˃˃ Fraud Trends for the Future – Digital Payments
