Analytics for every action, no matter what stage you’re in
Data, analytics, and technology differentiate the most successful credit unions.
No matter where you are in the process of incorporating data and analytics into your strategy, CU Rise has a solution that will produce powerful results.
Using state-of-the-art data mining techniques, CU Rise will examine your credit union’s rich repository of data and cultivate insights that drive greater member engagement and healthy, profitable portfolios. Our process is governed by your unique circumstances, needs, and goals. We deliver comprehensive solutions that can include:
- Detailed portfolio assessments to identify new product and service opportunities.
- In-depth analysis of member behavior across current product suite.
- Sophisticated and highly targeted campaigns that are easy to deploy and track.
- Ongoing monitoring and analysis of risks and fraud.
- Predictive analytics that accurately forecast member attrition and cross-sell opportunities, and recommend impactful retention strategies.
- Interactive reports that conduct and communicate advanced analysis against your custom metrics.
Custom Modeling to Deeply Explore Your Data
If your credit union wants to explore your data from new perspectives and extract high-impact insights, CU Rise will build the custom models that fit your goals. Powered by machine learning, our models grow more intelligent over time, empowering your credit union to implement continually optimized, highly effective strategies.
Examples of predictive models we can build include:
- Product models that identify the next best product to offer new and existing members
- Acquisition models that develop the marketing offers that will best attract new members.
- Membership models that segment members based on lifetime value.
- Risk models that reduce delinquencies and charge-offs and improve repayment
- Attrition models that identify disengaged members and effective re-engagement strategies.
- Loan approval models that build automated loan application processes while calculating future risks.