The instances of loyalty fraud has sharply risen in the past few years, and research reports have been showing that majority of loyalty program managers have experienced some form of fraud in their program. Such frauds put loyalty programs under serious risk much beyond the direct cost of fraud, such as lost customer, compromised customer data, reduced revenue etc. Loyalty program operators can no longer afford not taking proactive steps to detect and prevent fraud more smarter ways than before.
Traditionally, loyalty frauds have always been managed either completely manually or through well-planned rules built into the core loyalty management platform. However such measures are reactive in nature and could seriously hinder user experience. This is where advances in data science and machine learning can be effectively harnessed to detect and prevent sophisticated loyalty fraud.
In this white paper, we have covered
- The various types of loyalty fraud
- A machine learning based approach to detecting loyalty fraud
- How IBS can help you