Clarifire’s Jane Mason: To Survive, the Fittest Organizations Need AI—But That’s Not All

Jane Mason

Jane Mason is CEO and founder of Clarifire and the original architect behind CLARIFIRE, an application that brings all parties within mortgage servicing operations together onto one secure platform. She has years of leadership experience building process automation technology solutions for the financial services and mortgage industries. She has received numerous awards and accolades for her service to the mortgage industry and local business community, including the Mortgage Bankers Association’s 2020 Tech All-Stars Awards. Contact her at

Almost everybody has a basic understanding of Darwin’s theory of evolution and the concept of “survival of the fittest.” But what many people often forget is that the key to being “fit” is adaptability. It’s the species that are best able to adapt to changing conditions that are best able to survive.

Adaptability isn’t just important for all living things; it’s important for the financial sector, too, especially those in the mortgage industry, which is prone to highs, lows and chaotic events. It’s why the best organizations are forward-thinking and constantly adapting their business models and streamlining processes to lower their costs, provide customers with better service, and generate higher profits. And increasingly, they are leaning on AI and machine learning tools to enhance adaptability—because these technologies are themselves adaptable.

AI is more than a key resource for survival, too. It holds the potential to unleash productivity throughout the mortgage lifecycle by bringing origination and servicing sides of the business together. However, organizations looking to implement AI and ML technologies cannot do so in a vacuum. There’s another very important tool they need, too. 

How Artificial Intelligence Is Bridging Efficiency Gaps

In loan origination, AI and machine learning tools are increasingly being used to automate a wide range of historically manual processes more quickly and intelligently, from document collection, income verification, even underwriting. As a result, a growing number of forward-thinking lenders are beginning to reduce processing times, eliminate errors, and improve the overall efficiency of their operations. This not only helps to reduce costs but also allows lenders to close more loans and create happier customers.

AI and machine learning tools can also be used to analyze vast amounts of data in real-time, allowing lenders to identify and address potential issues before they become larger problems. This proactive approach to risk management can help lenders avoid costly errors, reduce fraud, and improve the quality of their loan portfolio.

More recently, AI and machine learning have had a similar, positive effect on mortgage servicing as well. For example, by combining AI with data analysis tools, lenders can identify borrowers who may be having trouble making payments and are at risk of default. Once these borrowers are identified, servicers can leverage automated workflow solutions to proactively reach out to offer assistance without any human involvement.

Financial institutions that utilize AI and machine learning tools to automate and streamline various loan underwriting and servicing processes are also better able to wean themselves off relying on manual tasks and paper-based processes. This has the effect of reducing errors and inconsistencies and leads to faster loan processing times and more efficient servicing.

The Fittest Create Customers for Life

It’s clear that AI is having an enormous impact on both origination and servicing processes. However, the future of AI in the mortgage industry lies in connecting these processes on both sides of the mortgage lifecycle. This not only creates more powerful, fulfilling experiences for homebuyers and existing homeowners, but also improves borrower retention and ultimately leads to greater profitability for mortgage organizations, including those within banks, credit unions and other financial services.

By leveraging AI and machine learning tools to combine the processes for originating mortgages and servicing them, organizations create a more seamless experience for borrowers. When borrowers have a smooth and easy experience, they are more likely to continue doing business with that lender.

For example, if a financial institution uses AI and machine learning to analyze a borrower’s past behavior and preferences, it can tailor its marketing campaigns and product offerings to that specific borrower’s needs. This can help increase customer loyalty and revenue as well as the chances that a borrower will continue doing business with that organization in the future.

Yet in order to effectively implement AI and machine learning tools and unleash their full potential, lenders and servicers need a strong technology foundation on which they can excel.

Creating the Right Environment

One of the dangers of trying to leverage AI too quickly and without the proper structures in place is that organizations will lack visibility into the logic required to automate specific processes and workflows. Before implementing AI, organizations need a trusted workflow engine that provides intelligence, data integrity, repeatable dynamic and logic results through validations, and process interconnectivity.

To break this down a little—to be effective, AI and machine learning tools need good data and lots of it. That means organizations need a workflow application that enables data readiness, results that can be depended on and are historically validated, as well as the ability to add or change business logic from the user interface whenever an organization needs to adapt and modify the way it uses data.

There are workflow engines that do this. The best enable users to display and measure key performance indicators (KPIs) by tagging or changing the tags on their data. Every interaction made by one user, or imports from third parties, changes data in the system in real-time and is visible to other users in real time, providing ultimate transparency. This enables organizations to better mitigate risks and costs while improving overall production quality and results.

So, while AI and machine learning tools are grabbing all the headlines right now, the most powerful tool in an organization’s toolbox is the platform on which such technologies are able to live, breathe and reach their full potential. And if you’re looking to implement such a platform so you can begin improving the customer experience and accelerate growth, it’s best not to wait around.

Adaptability and Procrastination Don’t Mix

With the recent drop in mortgage volume and the rise in loan production and servicing costs, it’s imperative for lenders and servicers to adapt quickly in order to stay competitive. Just like AI and the right workflow engine can increase efficiencies, improve profitability, and bridge the gap between origination and servicing, waiting too long to adopt emerging technologies can result in missed opportunities for cost savings and customer retention, leading to decreased revenue and market share.

The current state of the housing market demands that organizations—particularly lenders servicing their own loans—take advantage of every opportunity to streamline their processes and reduce costs, and not to waste any time doing so. Those that do procrastinate, on the other hand, will likely find themselves at a competitive disadvantage and struggling to keep up. This ultimately leads to greater costs and wasted efforts—the exact opposite of what every business desires.

If one were to look at mortgage companies as their own species, I think it’s pretty clear every member of the species is at a crossroads right now. Given the current housing market environment, with decreasing volumes and rising costs, some are going to make it, and others aren’t. This has been the case in previous downturns, and it’s going to happen again. In fact, it’s already happening.

Whether it’s AI, machine learning or workflow automation—or ideally, all three—the question every financial institution needs to be asking themselves is: How do we plan to adapt? Because by adapting, any species can thrive.

(Views expressed in this article do not necessarily reflect policy of the Mortgage Bankers Association, nor do they connote an MBA endorsement of a specific company, product or service. MBA NewsLink welcomes your submissions. Inquiries can be sent to NewsLink Editor Michael Tucker at or Editorial Manager Anneliese Mahoney at