By Boaz Reisman
Artificial intelligence (AI) and machine learning (ML) have come a long way—from powering self-driving cars to advancing scientific exploration. For credit unions, the practical benefits are closer to home: reducing costs, improving staff productivity, streamlining operations and enhancing the member experience.
When applied strategically, AI/ML platforms can automate repetitive tasks, such as document analysis and data validation, and help mortgage teams focus on higher-value activities. Unlike traditional rules-based systems, AI/ML tools use advanced algorithms to process and analyze massive amounts of data, continuously learning and improving over time.
However, before adopting AI/ML technology, credit unions need to plan thoughtfully and consider key factors to ensure success—particularly as regulatory oversight in lending continues to evolve. Here are four critical steps credit unions should take when evaluating AI solutions:
1. Assess Your Data Quality and Readiness
The strength of any AI/ML solution lies in the quality of the data powering it. Credit unions must ensure they have accurate, well-organized data to train AI models and deliver reliable results. Start by evaluating your data architecture and identifying gaps or inconsistencies. Building a robust data infrastructure that seamlessly integrates with AI tools is essential for improving performance and gaining meaningful insights.
2. Implement Performance Monitoring and Governance
AI/ML models require regular oversight to ensure their accuracy and relevance. Credit unions should establish a framework to monitor model performance and quickly identify any issues. This includes reviewing training data for bias, ensuring it reflects real-world production scenarios, and putting processes in place to evaluate new AI models before deployment. Having a governance plan allows credit unions to address errors and optimize performance proactively.
3. Educate Stakeholders Across the Organization
Introducing AI/ML technology will impact multiple departments, from compliance and legal to executive leadership and audit teams. Credit unions should prioritize internal education and communication to ensure all stakeholders understand the benefits, risks and limitations of AI/ML adoption. By fostering awareness and collaboration, credit unions can build confidence in the technology while ensuring alignment across the organization.
4. Ensure Vendor Transparency and Compliance
With increasing scrutiny from regulators, credit unions must choose technology partners that prioritize transparency and compliance. A responsible AI vendor should clearly explain how their models are built, what data sources are used, and how they address bias. Credit unions need to demand visibility into the development process, model performance, and reporting mechanisms to meet current and future regulatory expectations.
AI: A Tool to Enhance, Not Replace, Human Expertise
It’s important to remember that AI/ML isn’t a magic solution that can operate independently. While it can significantly boost efficiency and improve member satisfaction, human oversight remains essential. Mortgage teams must monitor, validate and continually train AI tools to ensure they deliver the desired outcomes.
For credit unions, AI offers an opportunity to enhance operational performance, streamline lending processes, and remain competitive in a crowded market. By aligning goals, data, and technology with future regulatory requirements, credit unions can safely adopt AI to deliver faster, more accurate results and better serve their members.
Plan Ahead to Unlock AI’s Potential
More credit unions are turning to AI/ML experts, like those at Dark Matter Technologies, to guide them through this transformation. With proper planning, investment, and trusted vendor partnerships, AI/ML can provide credit unions with a distinct competitive advantage and position them for future success.
Want to learn more? Check out our video interview with Blake Gibson, EVP of Product, Legal, and Compliance at Dark Matter Technologies, to discover how AI/ML is transforming mortgage lending for credit unions.