Souren Sarkar, CMB, of Nexval: How Robotic Process Automation Creates More Efficient Lending
Souren Sarkar, CMB, is founder and CEO of Nexval, Miami, a technology company specializing in mortgage automation processes and IT infrastructure upgrades. He has more than 25 years of experience as a technology leader in the mortgage and banking arena and is an expert at improving the performance and scalability of service-driven businesses using workflow automation. He can be reached at Souren.Sarkar@nexval.com.
With the housing market teetering on the edge of a new down cycle, I don’t know any lender that isn’t eager to cut costs in some way. The problem? Most lenders still rely too heavily on human effort, while concerns over the expense and operational complexities keep them from pulling the trigger on new technologies.
To be sure, the ROI on implementing technology is rarely clear. However, there is one common denominator behind the type of tools that actually do make a difference: they leverage robotic process automation (RPA), which has been shown to be the most powerful way to drastically reduce costs and improve overall efficiency.
In fact, RPA technologies have been proven to shrink loan origination and processing times by as much as 80% while increasing post-close quality control efficiencies by as much as 20%. More importantly, they empower lenders to free up resources to deliver better customer service to borrowers. And yet, there is relatively little discussion or understanding about how RPA actually works—let alone how powerful it can be.
RPA Has Come a Long Way
The purpose of RPA is to replace human effort either partially or fully, typically by automating low-variance, low-complexity tasks. Traditionally, this has been done by using a software robot (or “bot”) to complete routine tasks, such as checking for data entry errors in a loan application. However, RPA has advanced significantly in recent years. Newer technologies, including artificial intelligence (AI) and object recognition, now allow bots to perform more complex tasks, such as listening, understanding, and responding to borrower questions.
I often find lenders wondering about what processes can be improved by RPA and provide optimal ROI. The reality is that there are many processes that make good candidates for automation, such as cross-selling, document and report generation, and fraud alerts.
For example, customer service remains top of mind for most lenders, as it should. A recent McKinsey report found that a lender’s customer satisfaction level drops by 15 percentage points if they take more than 10 days to approve a borrower’s application. RPA is perfect for helping lenders provide faster responses to borrowers. This is done by using natural language processing (NLP) and configuring a bot to respond to frequently asked questions about timelines, forbearance, borrower verifications, and other borrower queries.
RPA tools can also leverage customer information to upsell and cross-sell services. Based on the information that a borrower provides when filling out a loan application, AI algorithms can be used to scan the lender’s product portfolio and recommend products and services that fit the borrower’s specific needs.
Reports are another area where RPA can be applied. In fact, producing reports based on the information and documents they receive from borrowers is one of the costliest and most time-consuming processes lenders perform. RPA allows lenders to automatically extract information from unstructured documents, index images, and archive everything in a centralized repository from which they can generate consolidated reports.
Combating fraud is yet another growing issue that costs lenders time and money. It usually takes a team of human analysts to look into individual alerts produced by a lender’s loan origination system (LOS) to identify problems. However, with RPA, a bot can be configured with appropriate business rules to automatically analyze alerts and detect false positives, as well as provide actionable reports.
While the benefits of deploying RPA are obvious, however, determining the best solution to fit individual needs is important. We’ve all made a purchase at some point or another that we later regret, and it frequently happens to lenders when selecting different technologies. For instance, often a lender will buy on-premise software only to discover later that they have the wrong infrastructure to maintain it. But there are some best practices to prevent buyer’s remorse.
First off, lenders need to figure out the specific type of RPA bots they need for specific mortgage tasks. Once this is determined, the automation script will need to be modified depending on whether the task is high or low in variability and complexity. AI will likely be needed for tasks that are more complex or where unstructured data is involved.
It’s also important to understand that in-house RPA initiatives frequently lose value rather quickly. Large banks, for instance, might want to build RPA solutions in-house because they think they will have better control over them. However, as a bank’s resources change and funds are reallocated toward new initiatives, these in-house RPA initiatives tend to fallout in the mid- to long-term. In reality, an outside RPA vendor with specific expertise in the mortgage industry is usually the better choice.
In most cases, the best approach with RPA is to start small and invest in governance. When it comes to automation, there are plenty of low-hanging fruits that can deliver quick returns without disrupting other processes or infrastructure. That being said, any RPA implementation, no matter how small, should be governed by a clear owner.
A Word of Caution
Considering the current market outlook, there’s no better time to adopt RPA than today. As I write this, interest rates are rising above 5% and the Mortgage Bankers Association is reporting a drop in mortgage applications. While margins are still healthy, a shrinking pool of homebuyers means lenders are facing severe cost pressures and layoffs, which can impact customer service levels.
There is no better time to leverage new RPA tools to handle essential, repetitive, and mundane tasks involved in mortgage processes, reduce the risk of human error and keep customers happy. It’s also vital for every lender to realize that an increasing number of their competitors will go all-in on automation technology at some point, if they haven’t already. In fact, if you look at the lenders gobbling up the most market share, almost all of them have heavily invested in automation.
Fortunately, there’s still time to figure out your needs and begin researching RPA solutions to develop a plan of action. As the Chinese proverb goes, “The best time to plant a tree was 20 years ago. The second-best time is now.” As even more intelligent automation becomes available, lenders that take a practical, strategic approach to implementing RPA will find success no matter which direction the housing market goes. Why shouldn’t your company be among them?
(Views expressed in this article do not necessarily reflect policy of the Mortgage Bankers Association, nor do they connote an MBA endorsement of a specific company, product or service. MBA NewsLink welcomes your submissions. Inquiries can be sent to Mike Sorohan, editor, at msorohan@mba.org; or Michael Tucker, editorial manager, at mtucker@mba.org.)
