Cut through the hype about machine learning and AI to make sound investment decisions
New attacks are happening with such speed and sophistication that rule-based and traditional risk scoring models cannot keep up; false positive rates are increasing while detection rates decrease.
Meanwhile, fraud detection and website security vendors are increasingly using the terms "machine learning" and "AI" to define their capabilities, leaving security and risk management leaders struggling to separate reality from hype.
This Gartner report to dive into key recommendations and insights for security and risk management leaders:
- The evolution and types of machine learning used in fraud prevention
- How to evaluate what your existing providers can offer
- Complementary implementations vs “Rip and Replace”
- Why advanced machine learning is not a silver bullet
The term "machine learning" is insufficient for an understanding of the use cases that will be enabled by an implementation, and clear success criteria must be defined and communicated.