Detecting Fraudulent Bookings of Online Travel Agencies with Unsupervised Machine Learning

Online fraud poses a relatively new threat to the revenues of companies. A way to detect and prevent fraudulent behavior is with the use of specific machine learning (ML) techniques. These anomaly detection techniques have been thoroughly studied, but the level of employment is not as high. The airline industry suffers from fraud by parties such as online travel agencies (OTAs). These agencies are commissioned by an airline carrier to sell its travel tickets. Through policy violations, they can illegitimately claim some of the airline’s revenue by offering cheaper fares to customers.