When you think of robots, what comes to mind? Many of us picture human-like machines such as Robby the Robot, C-3PO and R2D2, or even the robotic vacuum cleaners that are prevalent today. But not many of us are quite as aware of software robotics that are emerging, helping to automate business processes. It has been said that robots are the future of mortgage automation. Specifically, robotic process automation (RPA) software tools are helping with efficiency throughout the lending lifecycle.
Robots were created to eliminate the human operator, saving on labor costs. Another benefit is the speed at which systems can be deployed. In some cases, these “bots”, as they are known, can be deployed via configuration tools without any additional programming. This decreases overall time to market for new automation and it becomes more of a business-enabled event to make changes versus an IT-event that goes through rigorous change processes and deployment cycles. A number of players in the market offer chatbots and virtual agents to interact with humans.
And what if we could accurately predict when a specific loan needed an additional fraud check based on certain parameters? With newer RPA tools, specific, repeatable processes like QC and appraisal ordering can be automated even further than they are today. Many systems have had rules engines and automated service orders for quite some time. RPA can leverage disparate and unstructured data sources to determine proactive process changes for a specific loan scenario. Ultimately, overall error rates can be brought to zero with any task that would leverage RPA.
Machine learning techniques in conjunction with RPA, workflow management and load balancing can all become much more sophisticated as well. SLAs can be monitored in real time and adjusted accordingly for a given situation, thereby reflecting the complexity and size of any given task. Today, in most cases, a person has to change the SLA for a given work item manually. Using RPA, your knowledge workers can focus on more strategic items and only deal with the loan cases that require exception handling according to the loan parameters.
Another key area that RPA can be used for is the whole concept of RegTech. With constant changes to laws, guidelines, and rulings, and data that exists across multiple, disparate systems, RPA can ensure that customer, property, and other key data is available at the right place at the right time. In fact, data from origination, servicing, and core banking platforms along with data from other non-traditional sources like social platforms can help refine risk models to apply in a given situation and ensure full compliance with all applicable laws.
I’ll leave you with one final thought. PWC estimates that up to 38% of existing U.S. jobs are susceptible to AI and RPA by the early 2030s, but the nature of what humans do will change versus their roles disappearing altogether. RPA provides a level of automation that few companies have experienced as of yet. It allows lenders to become much more predictive and proactive to customers’ needs and wants via anticipatory models versus reactive as is the case in a number of operations today. Instead of replacing humans, RPA allows more focus on customer experience enhancements and strategic changes, improving the overall lending experience while gaining huge efficiencies and cost savings.