Customer Success Story

Wyndham Capital Mortgage creates a mortgage assembly line

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Wyndham Capital Mortgage

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  • Wyndham Capital Mortgage, Inc.
  • Charlotte, NC
  • Online lender with $1.5 billion in annual originations
  • ICE Mortgage Technology customer since 2008

Eliminating redundancy and inefficiency

Wyndham used Encompass to define over 500 business rules to drive loan origination workflow efficiencies. These customized workflows and milestones have helped minimize delays and speed the overall loan process.

61%

Increase in loans per production employee

16%

Decrease in average cost per loan

Increased

Pull-through and productivity

Enhanced

LO-borrower connections

Wyndham Capital Mortgage

Using Encompass® APIs, Wyndham Capital Mortgage has been able to identify key problems within the lending process and develop custom solutions. Automating both loan assigning and customer communication processes are just two ways that they’ve been able to maximize their resources and profitability at a crucial time in the mortgage industry.

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"Encompass is our information and automation hub that helps us process loans as quickly as possible. We couldn't have been as successful as we are today without implementing Encompass."

Jeff Douglas
Chief Executive Officer

Automating loan assignment

As a mortgage moves along throughout its lifecycle, it passes through multiple teams and departments. A human user is needed at each transition to manually assign the loan to the next phase. These manual assignments are resource-intensive, and are an entry point for errors and losses in efficiency. In addition, manual processes like these fail to account for variables like individual team members’ unique skill sets and loan complexity that automated processes are designed to factor in. Wyndham found solutions to these problems with Encompass APIs, and Auto Assigner. As soon as a loan moves out of a user’s pipeline, a new loan is assigned. Auto Assigner makes adding an infinite number of assignment criteria simple and quick. Criteria can be changed or updated in real-time so the organization can be intuitively responsive to changes in the market, or in their staff.

Automating customer communications

Two factors that are pivotal for success as a consumer direct lender are transparency and efficiency in communication. Borrowers need to receive personalized attention when making a big decision like securing a mortgage, and not feel like just another number. It became clear to Wyndham that they needed to implement a system of communication that would meet these borrower needs, without over-extending their resources. They needed to communicate loan requirements, statuses, and updates transparently and automatically. POS integrations allow their employees to stay in one system, eliminating redundancies and inefficiencies. This powers increased pull-through and operational productivity, as well as enhanced LO-borrower connections. These integrations also infuse trust and satisfaction into the entire loan process, as borrowers are empowered with increased transparency and access to information throughout the mortgage process.

The Challenge

Wyndham Capital Mortgage was on a mission to enhance their operational efficiencies by automating previously manual processes, including their internal loan assignments and borrower communications.

The Solution

They turned to ICE Mortgage Technology to leverage Encompass® APIs, SDK and third-party APIs to develop a Dynamic Auto Assigner tool, and integrate their point-of-sale (POS) system. The Dynamic Auto Assigner tool enabled WCM to remove all labor, ambiguity, and delays from loan assignments. In turn, the POS integration increased pull-through, LO connections, and operational productivity.

Benefits and Results

These benefits contributed to greater process automation for team-to-team loan assignments and borrower communications. As a result, WCM had some impressive gains over the MBA-reported averages: 2020 Q2 loans per production FTE was 4.5 (average of 2.8), 2020 Q2 average cost per loan was $6,732 (average of $8,057)

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