Empathetic Lending in an Era of Artificial Intelligence and Automation

What do your customers really want from a mortgage lender?

Buying a house or condominium is one of the most exciting and nerve-wracking purchases a customer can make. Purchasing a property represents comfort and security for their family and is an important element of their financial plan for the future.

Lenders should never underestimate the complexity and stress of applying for a mortgage. Customers are looking for a fast and efficient service that takes all their circumstances into account and wraps up their application as quickly and painlessly as possible.

To meet their customers’ needs it makes sense for lenders to reduce the physical and paper-based processes involved in mortgage originations. Automation and self-service options can remove manual data entry errors and costs, increase scalability, and improve efficiency. This in turn accelerates the time-to-close, which is the highest priority for both the borrower and the lender.

On the borrower’s side automated lending processes increase their satisfaction by providing instant pre-approval as well as visibility into their loan status and timeline. The borrower should know what stage their application has reached as they progress through the lending process and feel assured that they are fully informed throughout the journey. A self-service portal allows them access this information in real time and improves their overall borrowing experience.  Is artificial intelligence the solution for delivering the automation and personalization that borrowers are expecting from their financial institution?

AI could be a tool to increase mortgage lending efficiency.  But…

According to David Lykken, Founder and President of Transformational Mortgage Solutions, a true mortgage industry veteran with more than 50 years of expertise: “It could be argued that artificial intelligence has been used in mortgage underwriting for years. However, with recent advancements in AI, we will soon see 95+% of all loan decisions being made without human intervention and completed by AI.”

As with so many areas of business, artificial intelligence is having a positive impact on mortgage processes, such as underwriting and fraud detection.   On the less-positive side the initial training and learning models of AI can introduce elements of bias that could lead to discrimination against certain demographic groups or geographies.

Concerns about this potential bias have led to a slew of new regulations governing the use of AI in decision making, such as the US AI Bill of Rights. Lenders need to be aware of such regulations, as well as state-level initiatives in jurisdictions such as New York, Illinois, and Colorado.  So how should lenders such as credit unions and community banks best harness the power of AI and automation without losing their ability to understand the personal and specific needs of each and every customer?

Are Fintechs the solution?

A recent report compiled by East & Partners for Finastra found that the majority of National Association of Credit Management (NACM) affiliated US financial institutions were either considering and/or had already included capabilities provided by a fintech to fill gaps in their current mortgage offerings.

Fast and efficient integration with existing products, services and operations was a clear priority for these financial institutions. Three-quarters said they would choose fintechs that reduced the impact on client acquisition and retention, while almost two thirds would prioritize fintechs that would have the least effect on operations and customers.

So fintechs can be the solution, because they provide capabilities that integrate seamlessly with a financial institution’s own multi-channel services. Other factors include putting the customer first and providing an empathetic engagement experience, where the customer can be guided along each step of the process.

Not only does this meet customers’ expectations and reduce potential churn, but digital transformation leads to more revenue and growth for a financial institution, that can now reach beyond its physical locality to attract business from further afield. For example, Finastra’s client Hoyne Savings Bank, via implementation of automated onboarding technologies, now receives applications from a much wider range of customers, including those outside of their home state of Illinois.

What to look for in a Mortgage Lending Platform

To best serve a financial institution and their customers’ needs, a front-to-back mortgage lending platform (such as Finastra’s Mortgagebot) must be:

• Dynamic: meeting rising consumer demand for omni-channel, online self-serve options and streamline application, pricing, disclosure, and approval processes
• Accurate: maximizing branch opportunities with an efficient and seamless exchange of data
• Integrated: making each party in the lending process, including loan officers, processors, underwriters, and others more productive by making it easier to access existing data sources and systems
• Unified: providing a direct channel for consumers to use from the device of their choice, with an intuitive user experience
• Compliant: updating regulatory changes automatically and mitigating compliance complexity and bottlenecks
• Reliable and secure: protecting sensitive borrower information with redundant back-up systems, multi-level data security and independent rigorous audits.

With all these pieces in place loan origination activities become more efficient, transparent and customer centric.  Reduced response times and increased customer engagement lead to higher customer satisfaction and less churn.

To learn more about how a mortgage lending platform can improve efficiency and drive loan business growth visit:  www.finastra.com/solutions/originate-mortgagebot