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How RPA Can Improve Internal Processes, Not Just Automate Them: A Mortgage Breach Letter Case Study

As investment growth brings about increasingly large mortgage portfolios, many financial institutions often find themselves inundated with a proportional increase in resource strain and decrease in efficiency; such issues include management of mortgage breach letters, notices typically prerequisite to foreclosure proceedings that inform the borrower of a mortgage contract breach. Though mortgage data and breach letter processing differ by state and institution, both require labor resources and long hours, especially when conducted without automation.

Banks, investment firms, and other financial institutions allocate significant human capital and monetary resources toward collecting, organizing, and verifying data to determine who will receive a mortgage breach letter; the format of the data must also adhere to individual state requirements within the United States. As such, the overall process proves especially costly as overtime hours pile up in order to meet contractual Service Level Agreements (SLAs). With automation technologies such as Robotic Process Automation (RPA) and Optical Character Recognition (OCR), businesses can expedite breach letter processing and circumvent unnecessary resource expenditure.

Accelirate took a holistic approach to automating breach letter activity: rather than attempting to replicate the exact, human-dependent task in the Pre-Foreclosure Business Unit of this Asset Management Company, Accelirate looked at the overarching goal of the process and the required components to reach that goal. This holistic approach began with modularizing the initial input and determining the scope of the solution by identifying which U.S. States produced the majority of breach letters in order to more effectively focus automation efforts. The analysis facilitated the creation of a data map which increased processing efficacy by highlighting overlaps in both data points and State requirements. Through phased solution integration, modules strategically developed based on the data map were implemented in a phased manner which benefits compounded as their integration to production increased. This approach allowed for both preservation of data integrity and an exponential increase in management efficiency.

Through the utilization of RPA technology, Accelirate was able to not only automate the Breach Later Process, but improve the way the company currently was completing the task. The RPA bot gathers all necessary data points through a series of SQL queries and parses the datasets out based on the respective State requirements. Once parsed, the bot will then create each respective State’s breach letter with the data compiled and drop them into a network folder that is monitored by the mail room employees who manually print and send out the letters to their customers. Depending upon the State, registration on their unique State website is also required; using the previously gathered data the bot collected and saved, it effectively fills out the necessary fields to complete the registration. Once registered, the bot then logs and notifies the business of all completed transactions with the respective data being inputted for audit purposes.
By implementing this solution, Accelirate expanded the client’s audit capabilities and decreased both process time and backlog, allowing the client to meet all agreed-upon SLAs. Additionally, the automation decreased the amount of manual effort required, diminishing the need for the employees to work overtime to meet deadlines.

While automation technology has widespread applications, innovative implementation ultimately allows for customization to specific requirements and individual businesses. Despite organizational and processing differences even within a single industry, automation can adapt to situational parameters and significantly improve corporate growth.

To view the full in-depth Case Study on the Mortgage Breach Letter Automation that inspired this article, click here.