Highlights:
- Hear how using link analysis and a graph database enabled Marshmallow to recognise high-risk users and reduce fraud costs.
- Learn how Marshmallow countered false applications with incremental changes to the policy using a customised graph network.
- Discussion of how to draw insights on new users without data from previous spending habits.
- Demo of a visual representation of networks allowing us to see users linked by policies, quotes, claims, cancelled policies and shared emails, devices and contact information.
This webinar will be useful for merchants where spending habits are not typical and it can be more of a challenge to understand the end-user, such as gambling providers, subscription services or dating services.
Attendees will learn techniques for link analysis to avoid selling to high-risk users and therefore reduce costs.
