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Consider AI’s Less Discussed Benefits

Advanced technology injects speed into the mortgage process, but it goes beyond that

By Vaibhav Gupta

The COVID-19 pandemic posed a challenge to the banking, financial-services and insurance industries, and it prompted a digital transformation of the homebuying, selling and refinancing processes. The mortgage industry — which has been historically based on in-person relationships — quickly changed, forcing lenders and originators online as a result.

Businesses turned to advanced technologies such as artificial intelligence (AI) and machine learning to update operations and leverage emerging digital platforms to remain competitive in an evolving market, resulting in the creation of a transformative mortgage industry. As AI software advances and consumer preferences shift, it is only natural for all industries to embrace these new innovations that streamline business processes, eliminate errors, and manage and facilitate data. Car buying websites such as Carvana, credit-checking apps and other similar technologies have evolved to assist consumers in the seamless navigation of larger purchases.

Although some processes (such as property assessment) are difficult to completely digitize, the industry’s future is trending toward becoming increasingly digitized with each passing year.

The question arises as to whether the same ease can be achieved when purchasing a home. With updated consumer preferences and data driving mortgage decisions, lenders and the originators who work with them must use these new tools to succeed and remain relevant in this competitive market.
Although the average closing time for a mortgage is about 50 days, consumers expect closing times to be much shorter. The need to process loans and complete transactions as soon as possible will only become more pressing. One of the most significant advantages of incorporating advanced technology into the process is the reduction of the closing time. But there are numerous other advantages that are equally important and less widely discussed.
With so many readily available solutions that provide tangible benefits to mortgage companies, the return on investment for AI and machine-learning solutions is nearly instantaneous. Businesses should examine the many important benefits of deploying disruptive AI technology in the mortgage industry.

Consumer satisfaction

Consumer expectations are driving this rapid adoption rate. In 2020, ICE Mortgage Technology conducted a survey of consumers and discovered that 63% of those polled believed that an online mortgage process is easier than the traditional in-person process. Additionally, 70% of Generation Z respondents and 59% of millennials stated that mobile app offerings were a deciding factor when choosing a lender.
The new consumer market is conditioned to expect fast, almost instant gratification. Adopting document automation solutions can exponentially increase borrower satisfaction in a process such as mortgage lending, which can be time-consuming and redundant.
Banks, financial-services providers and mortgage institutions can drive operational efficiencies with future-ready digital mortgage solutions. Lenders can turn a multiday process of collecting hundreds of thousands of fields of data into one that lasts a few minutes simply by using this software. This benefits both lenders and borrowers, and it is arguably the most significant advantage of auto-mating the process.
By utilizing this technology, the lender can prioritize the critical human interaction component of this process rather than being consumed by tedious data sorting tasks and paperwork. Another advantage for the borrower experience is that this technology can assist lenders in better anticipating their needs, such as by using AI-powered chatbots.
This technology enables real-time problem-solving and client service, allowing consumers to be effectively guided through the lending process. Many consumers are conditioned to seek information online because of the pandemic’s effects and their ongoing need for instant gratification. Now that consumers are navigating processes that were once only conducted in person, this new digital process is becoming the preferred method of finding information.
Clients prefer instant responses at the click of a button versus having to wait for an in-person conversation. Having clear and simple platforms also reduces borrower confusion and streamlines the amount of communication between the borrower and the lender. This eliminates back-and-forth banter so that when conversations do occur, they are meaningful.

Error reduction

Processing hundreds of thousands of data points by hand leaves a large margin of error. While document processing software that converts images into characters is not new, the evolution of this technology into AI that mimics cognitive processing elevates the data processing experience like never before and significantly reduces the time it takes to close.
This level of technology also can be scalable on a case-by-case basis, allowing businesses of all sizes to benefit from this end-to-end, cloud-based solution. Because this technology can replicate cognitive processes, it can detect errors faster than humans — allowing lenders to take action as soon as the problems arise.
This digitization not only improves accuracy but also has significant environmental benefits. With the average mortgage application at 500 pages in length, digitizing the lending process reduces the amount of paper used while also lowering overall costs by eliminating the need for paper, printing supplies and carrier fees. Although paper may appear to be a minor expense, it becomes significant when yearly or even quarterly costs are considered.
The document digitization process greatly reduces the margin of error. Through increased and advanced cognitive processes, it also is able to create faster and more accurate results, all while scaling down the physical process of using hundreds of pages of paper.

Data potential

The success of the digitization process in any industry depends on how well organizations can mine their data. Because the mortgage industry is heavily reliant on data and documents, much of this information is contained within these documents. Before these future-ready digital solutions, the mortgage and banking industries had to go through a time-consuming and costly data mining process.
New technology, however, enables a faster and more cost-effective data collection process. It utilizes AI to comb through each digitized document in search of key indicators and data points that suggest the best properties. Furthermore, the ability to leverage this data in a shorter time frame enables a mortgage company to process more consumer data while saving on manual labor costs.
With the numerous advantages of this AI technology, the future is trending toward the realization of purely digital mortgages. Although some processes (such as property assessment) are difficult to completely digitize, the industry’s future is trending toward becoming increasingly digitized with each passing year, and there are good reasons for this.
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Mortgage companies must adopt these technologies as they evolve if they hope to not only survive but thrive in this ever-changing landscape. Only by employing the tools and resources available to them can they sustain a client-focused and efficient organization. This includes developing the essential end-to-end, accurate solution that dynamically automates important business operations in the mortgage industry. ●

Author

  • Vaibhav Gupta

    Vaibhav Gupta is the vice president and head of products at Visionet Systems. He has more than 20 years of experience in establishing tech businesses, building teams from the ground up and developing world-class products across multiple domains. Gupta owns the product and business strategy for the entire business, financial-services and insurance portfolio at Visionet. He leads a team of more than 70 engineers, data scientists, product managers and marketers spread across three time zones and two continents. Reach Gupta at info@visionet.com.

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