ML FDS - FRAUD DETECTION SYSTEM
Expert or rule-based solutions provide the first line of defense
Detecting cases of fraud mainly based on predefined criteria. While being simple and straightforward, this approach suffers from high false positive rates and more importantly is not resistant to complex fraud patterns. The Blindspot machine learning module provides the second line of defense, identifying new fraud types from data directly. Thanks to this data-first approach, a system learns continuously and adapts itself to evolving fraud sophistication.
Letting your data speak for itself
Empowered by Blindspot technology, takes your fraud management one step further. Our framework works in synergy with your rule-based system as an additional layer of security on top of it, making it easy and cost effective. Machine learning looks at data from multiple angles, spots complicated fraud patterns and prevents them in the future. As a result, your fraud prevention is robust, precise, resistant and adaptive.
Key Performance Indicators
Ability to learn and adapt without need of manual management of rules and black lists
Up to 76% accuracy in fraud detection
Up to 60% decrease in false positives
Thanks to Blindspot we have realized how to unlock the power of data and AI. What we found particularly helpful was the experience with claim data that demonstrated how we can leverage machine learning algorithms to empower our fraud detection process
We have been thinking about applying artificial intelligence to innovate our fraud detection process. Blindspot supported us in this initiative and demonstrated how machine learning can uplift our fraud detection efficiency.
JAN ŘEZNÍČEK, HEAD OF CLAIMS, ČSOB Pojištovna