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Case Study: Mutual of Omaha Mortgage
Submitted by Regal

October 1, 2026

Case Study: Mutual of Omaha Mortgage 

Mutual of Omaha Mortgage Moves From Manual Dialing to Conversations with Voice AI Agents

Mutual of Omaha Mortgage offers a variety of home financing and refinancing options, as well as industry-leading reverse mortgage products to help its customers through life’s transitions.

“We are moving from an outbound dialing operation to an inbound one. The agent makes contact, collects the borrower’s information, and hands the conversation to a licensed loan officer. Our loan officers spend their time in conversations rather than on a dial list.”  -- Kevin Griffith, VP, Sales Technology & Intelligent Platforms

IN NUMBERS

Voice AI agents let Mutual of Omaha Mortgage place more calls, faster, while maintaining positive contact sentiment.

70%+  Of handoffs connect the borrower to a licensed loan officer, live*

~5,000  Leads dialed per week**

80%  Positive contact sentiment**

*Mutual of Omaha Mortgage organic campaigns, 30 days to 8/19/26
**Regal data, not independently verified by Mutual of Omaha Mortgage 

THE CHALLENGE

Mutual of Omaha Mortgage ran outbound first. Licensed loan officers worked a progressive dialer, and the volume of that work set the shape of the day. Every hour spent dialing was an hour not spent with a borrower.

Kevin Griffith, VP, Sales Technology & Intelligent Platforms at Mutual of Omaha Mortgage, leads the sales technology function and is integral to how AI is applied across the mortgage division. He selected Regal, and his team builds the agents on the platform and tests them before any change reaches production.

WHY REGAL

Turning an outbound operation into an inbound one

Voice AI agents let Mutual of Omaha Mortgage place more calls, faster, and it is used that way. The larger change is what its loan officers spend the day doing. The AI agent takes the first outbound touch, and the loan officer picks up with a borrower already on the line rather than starting a call that may never connect.

A platform rather than a voice layer

Kevin did not want a conversational AI layer that left his team to build the surrounding workflow. He wanted a platform that could support the borrower conversation across the campaigns it runs, with the handoff to a loan officer built into it rather than bolted on.

Control after launch

Before choosing Regal, Kevin reviewed close to twenty vendors, and the deciding factor was not a feature checklist. It was who stayed in control of the agent after launch. “Being able to configure the agents with our own team, rather than route every change through a vendor, told me we would not be dependent on someone else’s roadmap,” he said. Regal’s Forward Deployed Engineers support that model, so the team keeps its independence without losing help when it needs it.

Keeping pace with the rules

Compliance is where the self-serve model earns its keep. The requirements around Voice AI agents are not uniform across states and they continue to change. Because the configuration sits with Kevin’s team rather than in a vendor queue, what the agent says can be changed the same day rather than waiting on a release.

“The rules around voice AI are still moving and they are not the same everywhere. Being able to change what the agent says ourselves, the same day, is what makes that manageable. Behind a vendor ticket queue we would always be a step behind.”  -- Kevin Griffith, VP, Sales Technology & Intelligent Platforms

DRIVING IMPACT WITH REGAL’S AI AGENTS

First contact and handoff on new leads

On the campaigns where the agent runs, a new inquiry no longer goes onto a dial list first. The agent makes contact, introduces the company, collects the information the borrower is willing to share, and hands the conversation to a loan officer. The agent screens no one out and makes no eligibility determination.

Changed by the team that runs it

Running these campaigns on one platform across teams with different requirements worked because Kevin’s team could adjust cadences and logic themselves rather than filing a ticket for every change, with a defined process before anything reaches production.

Read the full case study here. 

ABOUT REGAL

Founded in 2020, Regal is an enterprise voice AI agent platform for contact centers. Regal helps businesses build, deploy, and manage autonomous AI agents across sales, support, and operations teams.

 
 

 
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