Reimagining Credit Union Innovation with AI and Snowflake

In today’s fast-evolving digital landscape, Credit Unions must do more than keep up—they need to lead with innovation. Members expect personalized services, instant access to information and seamless experiences across every touchpoint. To meet these expectations, we’ve developed three AI-powered solutions using Snowflake, Power Automate, and cutting-edge LLMs to transform how Credit Unions can work with data.

1. Hyper-Personalized Auto Refinancing Offers

The Challenge:

Traditional refinancing campaigns rely on static rules and broad segmentation, resulting in low engagement and missed opportunities. Credit Unions often struggle to identify which members are eligible for refinancing—and when to reach out.

The Solution:

We built a predictive pipeline using Snowflake to unify loan data, credit behavior and market trends. A Python-based ML model predicts each member’s eligibility based on APR gaps, credit score patterns and income trends.

To personalize outreach, we integrated an AI Model to generate dynamic, insight-driven messages tailored to each member’s financial profile – whether they’re eligible or need guidance to become eligible.

We also developed a user-friendly web UI that enables teams to:

• Download predicted results.
• Refine search filters.
• Send personalized email/SMS communications directly from the interface.

Eligible members receive messages such as “You’re approved to lower your APR to 2.9%. Apply now!”, while ineligible members are sent guidance such as “Improve your credit score by 20 points to unlock better rates.” This tailored messaging ensures relevant, actionable communication that drives engagement.

Finally, integrating the AI Model to deliver these personalized messages via email and SMS, closing the loop from data to decision to delivery – fully automated.

Snowflake → Python model → UDF → AI Model → Email/SMS

Key Outcomes:

• Real-time, AI-driven personalization at scale.
• Reduced manual intervention with automated delivery.
• Higher refinance engagement and conversion.
• A blueprint to extend into other financial products like credit cards and HELOCs.

2. Democratizing Data Access with Natural Language Queries

The Challenge:

Imagine asking, “What were the top-performing loan products last quarter?” and instantly receiving accurate results – without writing a single SQL query. That’s what we built using Snowflake Cortex Analyst. With this solution, anyone, from a marketing executive to a branch manager, can query data in natural language and get instant answers.

Credit union data is rich but often locked behind complexity. Non-technical staff typically wait for reports or depend on analysts, creating delays and underutilized insights. We solved that with a text-to-SQL engine built on Cortex Analyst, securely integrated into Snowflake’s governed environment.

The Solution:

We’ve took our custom engine a step further by building and integrating this capability into a custom web application, developed entirely in-house. This required significant design, engineering and testing efforts to ensure it’s user-friendly, secure and scalable. It’s not just about using Cortex Analyst, it’s about delivering a complete, seamless experience tailored to the real-world needs of credit union teams.

Key outcomes:

• Empowers every department to explore and act on data.
• Reduces reliance on technical teams for routine queries.
• Enables faster decisions with real-time insights.
• Maintains data security with role-based access.

This isn't just another tool, it's a step toward conversational AI for Credit Unions, where users can not only ask questions but also receive proactive alerts and suggestions to support smarter decisions.

3. Smarter Document Handling with Document AI

The Challenge:

Despite digital ambitions, many credit unions still drown in paperwork –PDFs of 5300 reports, invoices, financial statements and more. Extracting data from these documents is slow, error-prone and often manual.

The Solution:

We leveraged Snowflake Document AI, powered by Arctic-TILT, to extract structured data from unstructured documents. By uploading a few sample PDFs and asking natural-language questions like “What are the total charge-offs?”, Document AI learns where to look and delivers consistent results.

To drive adoption, we built a custom no-code UI tailored for credit union users. No SQL, no scripts, just upload, point, click and extract. Designed for operations, compliance and audit teams, it makes document processing fast, simple and accessible to all.

Unlike heavy-duty solutions, this architecture avoids complicated pipelines that consume excess computing power. Instead, a simple SQL query can predict and return results, stored neatly in a database. All of it is handled in the backend.

Key Outcomes:

• Custom, easy-to-use UI offers a practical, scalable way to make sense of documents.
• No technical skills required.
• Smart extraction from paragraphs, dollar amounts and signatures.
• Lightweight architecture –no heavy ETL pipelines.
• Ongoing training lets the model improve over time.

Final Thoughts: One Unified Vision

Each of these innovations –personalized refinance offers, text-to-SQL data access and document intelligence –solves a unique challenge. But together, they reflect a single, strategic goal: Empowering credit unions to become truly data-driven without needing to be data experts.

We’re turning AI and modern data platforms into everyday tools for frontline staff, analysts and leadership, removing friction, reducing costs and enhancing member engagement.

Whether you're a data team looking to modernize infrastructure or a business user seeking more autonomy, these solutions show what's possible when the right tools come together with the right strategy.

Prahlad Hombali, Nilesh Pal, Kareem Basha Shaik, Dennis Dayakanth and Rajasekhar Shivakumar contributed to this article.