Forward-thinking business leaders across the mortgage industry continue to explore opportunities for leveraging artificial intelligence in everything from streamlining operational processes to creating an extraordinary customer experience. In 2024, the use of AI and machine learning was up 15 percent from the previous year, with 38 percent of lenders utilizing it, according to a study by Stratmor Group. This trend has grown in the past five years, with these numbers showing a significant increase.  

Some lenders are more hesitant when it comes to adopting AI as there is perceived complexity of integrating it into existing infrastructure, but these technologies are here to stay. When used correctly, AI technologies can offer great benefits and provide businesses with advances. An early focus on “heavy preparation and light experimentation” can help set lenders up for success, says Sandeepa Sasimohan, vice president of product automation at ServiceLink.

How can lenders go about putting “first things first” as they embark upon their AI journey? They should consider a change-management mindset and ask themselves these five questions:

1. Where does AI fit into our existing business roadmap?
2. What can be home-grown versus what needs to be supplied externally?
3. What teams and extended teams (external partners and suppliers) must be in place?
4. What metrics will define success?
5. How will we create a lifecycle model so there is neither a delay nor a rush in pivoting toward the next AI wave as it keeps evolving?

Lenders should also be reassured that AI tools do not come from some “kaboom moment,” emerging from a lab somewhere with no security checks as there is a large, solid chain of de-risking agents, including universities and research centers, that engage in years or even decades of research before AI functionalities become mainstream. Tech-enabled service providers take de-risking through the final stretch, carefully scrutinizing and testing any use of AI before applying it to their core service offerings.

AI trends taking hold

As AI technology continues to advance in evolutionary and revolutionary ways, Sasimohan shares insights into the top five AI-driven mortgage industry trends she expects to see throughout the year.

1. Broader adoption of generative AI and predictive AI

The boom of ChatGPT portends a growing appetite for other forms of AI. Two forms that can prove to be useful in this industry are generative AI and predictive AI. While both types of AI are fueled by machine learning, they differ in the results they can provide. Generative AI can generate content such as text, images, video and software code after looking at and understanding patterns while predictive AI looks at historical patterns and forecasts likely outcomes. Generative and Predictive AI have different purposes to serve. Generative to create outputs and Predictive to forecast outcomes.

For example, you could leverage traditional AI is to help predict whether interest rates will go up or down. You could then leverage generative AI to add a recommendation: “Because interest rates are X, you might consider applying this percentage of your business to home equity and this percentage to first mortgage.”

Sasimohan adds that while interest in generative AI is quite high, traditional AI continues to have many important uses in mortgage lending processes. “Traditional AI can help lenders understand trends and forecast consumer behaviors. It can provide insights for making the consumer experience more efficient, transparent and seamless.”

Mass customization is likely to become more mainstream as AI can zero in on details essential to a particular loan — whether the borrower is putting 20% down on the mortgage, for example — to create a niche, individualized experience tailored to their needs. In this example, a series of mechanisms are set in motion to determine whether the loan will be denied outright, relieved outright, or if there’s a conditional in-between. Those conditions can form quite a deep decision tree, with further conditions triggered upstream. AI enables the individual to navigate a rather complicated decision tree that could have taken weeks or months but instead took minutes because an intelligent, highly scalable virtual agent managed it and presented a menu of solutions.”

2. Greater reliance on predictive risk analysis

Risk is, of course, a critical component of originating and servicing loans. Predictive risk analysis uses AI to track multiple interactive variables and act as a “crystal ball” for lenders and servicers. “These applications tend to exceed, by far, the number of dimensions or criteria along which humans are equipped to perform well,” says Sasimohan.

3. Sharper focus on AI legislation

In addition to the technological trends we’ve seen throughout the year, Sasimohan looks for a strong focus on the legislative aspects of AI. “With all of its amazing abilities, AI comes with some ethical and legislative issues in terms of how and which data we need to protect,” she said. “A growing number of corporations will be adopting policies this year to keep their AI practices in check.”

ServiceLink: A pioneer and thought leader in AI

As AI continues to advance at an unprecedented pace, lenders looking to tap into its power don’t have to go it alone. ServiceLink has been leveraging automation and machine learning through its EXOS platform for a long time, always ensuring that the technology is mature and vetted before offering it to client partners. An AI development framework strengthened through years of fine-tuning enables ServiceLink to balance the adoption of proven AI-driven tools with the exploration and testing of bleeding-edge technologies that hold the potential to propel the mortgage industry forward.

From the lender perspective, the ServiceLink team understands the need for a measured, integrated approach that maximizes results while minimizing risk. “AI success depends on having the right data in the right format, at the right place and time. It follows that lenders need to use the right platform rather than pursuing AI in piecemeal fashion on their own,” says Sasimohan. The quality and depth of data being used is essential as any product is only as strong as the data it builds off. ServiceLink’s advantage, for example, lies in having access to historical data aggregated by Fidelity National Financial – including the data on millions of previously insured records and parcels of land..

ServiceLink’s commitment to adopting the best emerging AI technologies is evidenced by the substantial investments over the years, Sasimohan says. “Staying on the leading edge of AI requires sizable financial investments as well as a deep understanding of both the technology and the industry. We know AI and have decades of industry experience. With compliance and regulatory bounds always in mind, we make sure that security is first and foremost, and that the AI models being built are sustainable in the long term. That sets us apart.”

As AI continues to evolve and gain traction in the mortgage industry, it is something we anticipate being utilized more. Where does AI fit into your roadmap?

To learn more about how ServiceLink’s approach to innovation, contact us here.

‍