How AI, RPA Promise to Revolutionize the Mortgage Industry?

Mortgage Lending

Mortgage Lending

Understanding digital lending and the changing landscape of Mortgage.

The ongoing digital revolution is increasingly transforming business models across diverse industry verticals. The mortgage industry is not an exception as customers seemingly expect similar enhanced experiences from their lenders. Technologies such as artificial intelligence, machine learning, and robotics process automation (RPA), among others are significantly contributing to the transformation of the industry by addressing issues ranging from customer experience, asset quality and risk, and regulatory compliance, to efficiency and cost repression.

Such technologies are also leading the digitalization within the industry, giving the rise of digital mortgage. In its report, KPMG noted that a digital mortgage transformation yields benefits across both growth and efficiency value levers. Moreover, shifting to a digital lending model will have a quantifiable bottom-line impact through expanding and stimulating the sales funnel while minimizing costs with greater process efficiency.


Boosting Mortgage Lending with AI

Today’s borrowers expect faster, efficient and error-free mortgage lending. In this way, mortgage firms must reconsider their processes to be processed at a quicker time. Fortunately, the advances of AI will have a positive impact on the industry, as the technology has the potential to automate the lending process. Applications of AI can also help mortgage lenders to better analyze borrowers on their ability to repay loans. The technology accesses a greater breadth and depth of customer information, and then provide a fuller picture of applicants to a lender firm.

But not all the time AI can give full insight about a borrower as most customers may not provide more personal information. According to a survey by the Harris Poll, 70 percent of Americans would gladly provide more personal information if it results in a fairer credit decision. Conversely, the same percentage wish there were more ways besides the three-digit score to prove they were creditworthy.

In addition to this, there is a major concern for a majority of lenders looking to implement AI is the fear of bias against certain people. To control and curb this state, regulators and lawmakers are prudently looking at how lenders and other financial services providers are employing AI and machine learning credit models.

Despite this, many executives see AI as an effective technology for their variety of business objectives. According to the report, almost 55 percent of executives reported that the technology will make their firm and the industry overall more competitive. On the other hand, some say AI will assist them in lessening operating costs, delivering personalized customer experiences, improving customer experiences and minimizing cycle times.


RPA to Expedite Mortgage Processing

With making significant improvements in enabling customers to move to digital channels and more self-service options within mortgage lending, lenders can improve customer satisfaction, customer retention, brand value and, eventually sales.

Banking practices, which involve a lot of paper works, always be susceptible to errors and data losses. Even the slightest error can slow down the process and complicate matters, creating a strain over both financial institutions and customers.

The introduction of RPA for such practices can alleviate these sorts of challenges while easing workloads from human staff. The technology can significantly improve the mortgage loan experience by detecting and resolving errors, automating lending processes and clearing the bottlenecks that often delay mortgage origination. Considering reports, RPA is likely to witness a growth at a CAGR of nearly 60.5 percent from US$0.18 billion in 2013 to US$5 billion in 2020.