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Transforming the Mortgage Business in 3 Quality Steps

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For too long, banks and financial firms were stuck with the status quo when it came to mortgages and loans, but change has been dramatic over the last few years.

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The time it takes to process a mortgage or a loan has been a source of frustration for many years, both for consumers and the originators of the loans. Yet despite that shared anger, there never seemed to be a way to speed up the process while still keeping costs under control. However, the technological breakthroughs of the last few years have convinced many experts that change is finally here.

The Benefits of Agile Mortgages

Artificial intelligence and machine learning are behind the improved risk management, carefully tailored services, and better decision making, which research firm McKinsey predicts “could generate value of more than $250 billion in the banking industry.”

The key to 21st-century success is the concept of agility, which can be defined as “using data and analytics to continuously source promising opportunities or solutions to problems in real time, deploying tests quickly, evaluating the results, and rapidly iterating.”

Applying agile thinking to mortgages and loans is driving the improvements that are transforming the industry.

Agile mortgages from AI Foundry are changing what consumers expect from a loan, including:

  • Increasing accuracy levels to 90%
  • Reducing loan processing times by 50%
  • Speeding mortgage approvals from weeks to hours
  • Achieving average savings of $500-$600 per loan.

Let’s take a closer look at the behind-the-scenes technology that is revolutionizing the ways business is being done today.

Machine Learning

Thanks to the big data revolution and the dramatic reduction in the cost of computing power, machine learning has moved from the fringes of very specialized processes into mainstream banking and financial services. McKinsey explains how machine learning algorithms “combine a massive set of decision trees (i.e., a decision-making model that breaks out individual decisions and possible consequences, also known as “learners”) to create an accurate model. By churning through these learners at high speeds, ML models are able to find “hidden” patterns, particularly in unstructured data that common statistical tools miss.”

Artificial Intelligence

There is a tendency for people to conflate artificial intelligence (AI) and machine learning (ML), but there are subtle differences between the two. AI is the capability of a machine to imitate intelligent human behavior, while machine learning implies that a machine will get better and better when it is faced with repeating a task over and over.

Using AI for agile mortgages delivers faster ways to perform classification with over 90% accuracy, a sophisticated engine which enables lenders to configure a library of rules that can be aligned with different areas of the organization, and a cognitive business automation platform upon which these processes are built.

Digital One Office

Bringing together the front- and back-end office processes into one seamless system is at the heart of AI Foundry’s Digital One Office. According to the Digital One playbook, “This end-to-end automated approach manages the entire loan process from ingesting required loan documents, processing, and underwriting to mortgage post-closing, selling, and servicing while efficiently connecting the front and back office operations for a superior customer experience.”

Taken together, these processes form the backbone of a new paradigm that is shifting the mortgage and loan process in major ways.

Keeping Costs Down Is Fundamental

Speed and efficiency are vital, but they are meaningless if costs skyrocket at the same time.

Emily Nash-Walker is the Head of Solution Architecture at AI Foundry. In a recent webinar, she noted that “on average, $8,900 is spent to process a loan. Of that, roughly $1,800 is spent on loan compliance.” This begs the question, “How can your business spend as much of that money as possible on data quality and loan activity?”

Costs include manually sorting documents, locating data fields and entering them into bank systems, verifying and reconciling information, and many more tasks that can be completed better and faster with the technologies we have been discussing.

At the same time that this technology is changing what is possible, the business environment is becoming more and more challenging, causing:

  • Rising interest rates, which have resulted in revenue from originations falling by 39% from Q3 2016 to Q3 2018. 
  • Rising origination costs, including a 68% decline in net production income per loan.
  • Increasing market fragmentation.

In this complex business environment, it’s clear that what is needed is the kind of technology that can improve data accuracy as well as help you compete faster and win while providing meaningful savings at the same time.

Moving Beyond the Status Quo

With the right approach and the right partners, any banks or financial institutions that provide loans can access this technology. It requires some flexibility around the rigid pipelines and workflows that define this kind of work as well as a company culture that encourages collaboration and is comfortable in retraining staff to make use of new technologies.

With that kind of approach, companies are well positioned to make better decisions, gather more accurate data, and achieve the kind of efficiency that impresses consumers and wins a loyal customer base.

To find out how these technologies can make an impact in your organization, please contact AI Foundry today to set up a consultation.   

Want to learn more?  Listen to a recording of our Product Spotlight: Changing the Game with Agile Mortgages 

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