Machine Learning Helps Credit Unions Become More Personal, Secure
- The usage of AI, and its subset machine learning, is a rising trend among financial institutions as they seek to improve customer satisfaction, reduce inefficiencies and fight fraud.
- Jerry Melnick, president/CEO of the San Mateo, Calif.-based machine-learning analytics firm SIOS, defined machine learning as a type of artificial intelligence and method of data analysis that uses algorithms to draw conclusions, make predictions or learn without additional programming.
- Sanchez explained, “Part of artificial intelligence is predictive analytics, which you can say is the same as machine learning.”
- The Hoboken, N.J.-based NICE Actimize’s new product, ActimizeWatch, is a cloud-based analytics optimization solution, which leverages machine learning and the cloud to provide proactive fraud analytics optimization and consortium data sharing.
- “All of our customers, whether they have an on premise or cloud solution, continually send us transactional data and we continually monitor threat data, identifying fraud patterns and using machine learning to optimize analytics very quickly,” Little said.
AI is a rising trend among CUs as they seek to improve member service, reduce inefficiencies and fight fraud.
@jaypalter: #MachineLearning helps #creditunions become more personal and secure
via @DeepLearn007 #AI
The irony is not lost on how nonhuman interaction using machine-learning capabilities in financial technology could supply a more personalized member experience, as well as added security and operations performance.
The usage of AI, and its subset machine learning, is a rising trend among financial institutions as they seek to improve customer satisfaction, reduce inefficiencies and fight fraud.