#4081: All In Credit Union Experiences 90% Faster Loan Decision Making with Zest AI's Lulu...

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All In Credit Union’s SVP Sales and Lending Todd Peeples joined us on the show to sharin the credit union's problem-solution-results experience using Zest AI's Lulu, their generative AI lending intelligence companion, into its lending workflow.

Before LuLu, Todd shared how All In worked with multiple business intelligence tools, spreadsheets, and platforms. Lulu changed all that, allowing the credit union to consolidate all three to improve efficiency for the team.

He also talked about how much of a difference LuLu has made in terms of time and resources spent on reporting and analysis compared to their old way of working.

In addition, Todd shared concerns about using generative AI around security and governance but added how did Zest AI - and specifically LuLu - helped ease those concerns while delivering powerful insights.

Zest AI's LuLu gives credit unions access to NCUA call reports, HMDA data, macroeconomic trends, proprietary metrics - all in a secure, unified platform. He touched on how having all this information has improved All In's strategy and operational agility.

When added all up - tool consolidation, reporting speed, decision-making agility - Todd talked about the ROI of LuLu, describing the value it’s creating for members and employees. Results to date at All In include:

• 50% of reporting tools can potentially be consolidated 
• 80% less time and staff needed for analysis and reporting
• 90% faster decision making -- saving time from analysis to action

Looking ahead, Todd shared what possibilities excite him most using LuLu -- adding how he expects LuLu to continue evolving their lending ecosystem.

Q&A summary
What is the role of Lulu in the automated underwriting process at All In Credit Union?
Lulu, Zest AI's generative AI lending intelligence companion, has been integrated into All In Credit Union's automated underwriting workflow to enhance efficiency and streamline data access.
How has the introduction of Lulu improved data access for the credit union's staff?
Lulu allows staff to input normal questions and receive instantaneous data responses, reducing the need for multiple tools and saving significant time in data retrieval.
What were the challenges faced by All In Credit Union before adopting Lulu?
Before Lulu, the credit union relied on multiple business intelligence tools and had to go through lengthy processes to request data from IT, often taking up to two weeks.
What security measures does Zest AI implement to address concerns about generative AI?
Zest AI ensures data security by segregating sensitive information, not allowing access to personal identifiable information (PII), and using aggregated data for insights.
Can you provide an example of how Lulu has directly impacted policy recommendations at All In Credit Union?
After an NCUA fair lending exam, Lulu provided recommendations that matched exactly what the NCUA suggested, demonstrating its effectiveness in policy enhancement.
What future developments are anticipated for Lulu within the lending ecosystem?
Lulu is expected to expand its data components and functionalities, providing even broader benefits across various departments within the credit union.

Check it out and let us know your thoughts. And be sure to watch the entire episode below for all the details.