Neuton
Empowering Credit Unions for the Future

The uniqueness of each credit union is in its relationship with members. Make this relationship truly personal using AI technology.
Neuton.AI – No Code Artificial Intelligence Platform for Credit Unions
Check out a 2-minute video about how it works on the example of the member churn prediction
Boost engagement with members and reduce churn.
Personalize products and services
Anticipate members’ requirements and improve member experience
Prevent risk of losses via customer risk ratings
Member Models – The Foundation for Personalization
«As we started shifting to a cashless environment, daily cash withdrawal limits became hard to predict. By leveraging Neuton, we were able to predict the likelihood for certain groups of members to require higher cash limits and raise our ATM limits in accordance with their needs.»
Todd Lindemann
Senior Vice President of Payments for Redwood Credit Union
«What makes our members stay with Redwood CU is that we anticipate their needs and we find the solution that helps them with their financial lives. AI helps us drive that making us successful.»
Tony Hildesheim
Chief Administrative Officer, Redwood Credit Union
«According to the recent research by the Boston Consulting Group over 70% of  data and digital initiatives fail to deliver on the promised value.»
Naveen Jain
Founder and President, CULytics
«Credit Unions are slower to adopt new technologies, so the time of production becomes more important. In this case, finding the solution partners who can assist in developing new capabilities and nurturing new technologies is essential.»
Jay Lauer
Senior Innovation Strategist at PSCU
«Credit Unions are mission-based, so their main competitive advantage is based on providing personalized services to clients. Leveraging machine learning, credit unions can gain insights into the major problems that their clients face and offer the best solution.»
Anne Legg
The founder and principal of Thrive Strategic Services
Personalization in Action.
Dynamic ATM Limits Case Study
Vasudevan Srinivasan
Data Programming Manager at Redwood
Challenge
During last year more then 160K transactions reached their static limit of ATM withdrawals.
Increased Member contacts with Branches & Member Service Center without risk of negative member experience.
Solution
Implement Member Based Risk rating model leveraging ML Based Predictive models.
Implement Dynamic ATM Withdrawal limit service model
Result
Reduced static limit breaches by 20%
Reduced customer service contacts by over 10%
Enhanced customer digital experience
Launch AI Driven Solutions Automatically
without any programming skills and data science knowledge
Upload your Data
Relax while everything is done automatically
Make predictions explore insights
Why existing tools are not enough?
The lack flexibility to account for personalization on member level
Tools such as FICO do not reflect the members behavior within our institution
FICO & typical BI Tools provide a historical view behavior
Typically does not have a forward looking view that results in a specific outcome or action
Laverage Neuton.ai to Boost Engagement with Your Members!
Lack of flexibility to account for personalization on member level
Tools such as FICO do not fully reflect the members’ behavior
FICO & typical BI Tools provide a historical view behavior, however, they fail to predict outcomes, resulting from specific actions
Lack of explainability and transparency
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