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Optimizing Decisions for Credit Union Members
Beyond the Score: How Personalized Offers Can Help Modernize CU Lending
Watch The WCUC 2024 Panel Discussion
New Whitepaper: Innovation and Inclusion in AI Credit Risk Models
Podcast: Innovation and Inclusion in Credit Risk Models - Listen Now
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Reactive vs. Proactive Credit Offers, a White Paper Excerpt

Lending technology has come a long way in the last ten years. We’ve seen tools that automate underwriting, simplify applications, and use alternative data to refine credit scoring. It’s all

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Beyond the Score: How Personalized Offers Can Help Modernize CU Lending

Attendee Takeaways: The urgent need for credit unions to evolve how they make decisions How current AI scores can negatively impact the member experience The definition of decision optimization and

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Optimizing Credit Union Member Performance

Credit Unions have to make smarter member decisions as their community moves to the digital-first world. Decision Optimization tools are here to help.

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Innovation and Inclusion in AI Credit Risk Models, a White Paper Excerpt

Enhancing the credit union member experience and access with real-time personalized lending Building upon the “people helping people” credit union philosophy, C-level decision-makers must continually rethink the member experience. Increasingly,

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Leverage AI and Banking Data to Attract New Members

Here’s an insightful podcast featuring Tom Tobin, the founder and CEO of Modelshop, a pioneering FinTech company dedicated to using large language models to create software automation. Tom will share

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Using AI to Create Centralized Member Decision Strategies That Deepen Member Relations

Attendee Takeaways: The power of new alternative data How to start using AI modeling without coders or data scientists Key benefits such as better credit decisions, improve efficiency, personalize loan

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For a decade, our clients have used our offer automation platform to provide personalized and risk-based financial products to their customers in real-time without having to rip or replace their existing tech-stack.

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