Why do mortgage applications take weeks and sometimes months? Digital-native customers, such as millennials, are using their mobile devices to order rides, request food delivery, and make international money transfers and are now expecting the same level of speed when applying for a home mortgage loan.
Mortgage lending institutions need to harness artificial intelligence (AI) to accelerate responsiveness, shorten the mortgage application process, and protect both the lender and the borrower from fraud.
In an earlier era, customers only wanted the best product at the best price from their lending institutions, but speed was less important. Today, more millennials are pursuing home ownership than ever before. As millennials age and grow in their careers, they're acquiring more purchasing power, shopping for mortgages online, and entering the market well prepared.
According to the National Association of Realtors Research Group, 25% of millennials purchased homes for $250,000 and higher in the past year in the U.S. And this trend is only growing in 2019. Banks and mortgage lending institutions must address the digital nature of today’s buyers by adding AI-powered, intelligent Robotic Process Automation (RPA) to accelerate all bank processes and the customer experience.
Due to the complex nature of mortgage processes, getting a home loan can take some time. Many of the lending organizations rely on manual processing of multipage loan documents, pay stubs, W2s, and additional loan documents. Lending institutions must manually, and often painstakingly, extract information from these documents and input them into databases, such as enterprise resource planning (ERP) systems to be processed further.
Implementing an agile AI and RPA system doesn’t mean embracing chaos. In fact, a system that’s well designed observes well-defined rules and ensures institutional safety. AI-powered RPA can help banks solve specific processing problems and increase productivity by 20%, freeing employees to focus on building relationships with customers.
According to National Mortgage News, 72% of all home loan lenders agree technology will help them stand out from their competition. To process mortgage applications, banks today deal with complex legacy systems, disparate databases, and spreadsheets, all of which involve lots of physical and digital documents.
This is where AI combined with RPA can make banking more efficient at delivering home loans for qualified customers. RPA brings numerous opportunities for adding agility to multiple processes. Since RPA is rule-based, it can accelerate loan eligibility verification based on predefined criteria that every application is evaluated for.
We live in a world of risk that needs to be judiciously monitored. Mortgage lending requires constant risk assessment and compliance oversight. Automation streamlines operations and ensures safeguards are in place to monitor and report exceptions to avoid unwanted surprises to either banks or customers.
Automation immediately reduces manual errors, such as keying mistakes, misapplied rules, etc. Risk monitoring and reporting also become easier to scale with RPA.
The advantages of RPA are clear and immediate: Agility in bank processes is better for customers and staff, who are able to focus on customer relations rather than mundane, repetitive tasks. In combination, this improves efficiency while reducing operational costs. Here are four advantages to introducing automation in your ecosystem:
Banks can start streamlining operations
Detect fraud or reduce defaults
Augment mortgage servicing with AI
Delight your customers with award-winning service
The rise of digital customers — accustomed to Netflix, Uber, Instagram, and Google — is leading banks to implement a complete agile system, from mortgage qualification to closing. Leaders in banking who are adding AI and RPA are making their customer journey faster, more accurate, and effective while building brand loyalty for retaining their top-end customers for the lifetime of the loan.
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Brinda Sreedhar is a product marketing manager.