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5 Examples of Cutting-edge Tools to Reinvent Your Mortgage Tech Stack

Not only does technology provide a better customer experience, but it is proven to create a more efficient and less risky lending process from beginning to end

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  • Written by  John Heck, Senior Advisor of Lending Solutions at Capacity
 
 
5 Examples of Cutting-edge Tools to Reinvent Your Mortgage Tech Stack

The need for digital experiences is sweeping across all industries — especially under current circumstances. The mortgage industry is certainly no exception. Not only does technology provide a better customer experience, but it is proven to create a more efficient and less risky lending process from beginning to end. The Federal Reserve Bank of New York found that FinTech-driven lenders process mortgage applications 20% faster than those using traditional processes while also decreasing their default rate by 25%.

However, it is one thing to talk about modernizing the mortgage experience and another to bring the lending process into the modern era. To keep up with expectations of today’s savvy borrowers and lenders, you must reinvent your mortgage tech stack with the most innovative tools available.

1. Financial management tools

With a transactional financial management tool, organizations can empower borrowers throughout their entire homeownership journey. This technology can aggregate the consumer’s financial data -- like assets, income credit, taxes, insurance and more -- and streamline the process with intelligent analytics so it can provide recommendations based on the user’s full financial profile.

2. Intelligence and retention systems

By identifying when a lead becomes qualified, an automated borrower intelligence and retention system tailored to the mortgage industry can instantly alert lenders when a borrower is ready for a loan. Providing loan officers with the visibility they need to identify when potential borrowers have changes to their credit, are shopping with a competitor or list their home for sales, automated intelligence and retention systems help LOs know where their customers are in their homeownership journey.

3. Anonymous shopping platforms

An anonymous mortgage shopping platform can create a confidential experience for borrowers interested in comparing mortgage rates or alternative mortgage lead generation. Instead of having LOs reach out to borrowers with cold calls, they can move at their own pace and uncover the information they need to move their process forward. It takes the pressure off of borrowers to engage with your team until they’re ready to talk.

4. Chatbots

By automating support with AI, chatbots are one of the best tools for improving the lending experience. Instead of overwhelming lenders with questions about the process, their current status and more, chatbots have the power to automate responses to these questions based on specific insights about the borrower so they can get the requested information instantly.

5. Point-of-sale solutions

A point-of-sales (POS) solution can assist banks, credit unions, and even non-bank lenders in diving deeper into the mortgage origination process, at a significantly faster rate. POS solutions armed with big data and process automation can move borrowers and originators through application to appraisal in a matter of minutes.

This list only scratches the surface of innovative mortgage technology available today. Mortgage professionals have a large selection of different tools to fuel their mortgage tech stack. The industry is full of useful mortgage technology dedicated to enhancing the lending process for both borrowers and loan officers. By identifying which solutions are most appropriate for your borrowers and loan officers, mortgage leaders can establish a smoother, faster and better lending process for all parties involved.


John Heck is the Senior Advisor of Lending Solutions at Capacit. He is an experienced executive with a deep understanding of complex platform technology including AI, Natural Language Processing, Machine Learning, Cloud, Digitization and Data Analytics.

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