A loan application has to pass through stakeholders involved in a typical mortgage loan life cycle. This prolongs the time taken to close a loan to over 5 weeks.
This time can get longer because of factors such as economic volatility, a critical resource quitting who was also handling a particular loan, among others.
Today, time is one of the key factors that differentiates ability of one lender from others. Moreover, the TILA-RESPA Integrated Disclosure (TRID) regulations mandate setting specific timelines that lenders must meet to release loan closure estimates.
It is imperative, that lenders get rid of manual and paper-based processes and leverage automation. This is the key to execute mortgage processes efficiently while saving a significant amount of time.
In this article, we explore how mortgage process automation aid lenders to save time.
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Mortgage Process Automation Application to Save Lenders Time
Automated Fraud Detection
Manual fraud detection involves a series of elaborate steps that take considerable time to complete. The steps involve accessing external web portals, checking applicants’ backgrounds, checking document accuracy, updating system with risk assessment completion, among others.
When fraud detection tools enabled by predictive analytics is integrated with lenders’ loan origination system (LOS), it automates risk determination of loan applicants.
All the risk assessment activities are recreated as rule-based workflows. These workflows are efficiently executed by RPA. This brings considerable acceleration in the process, thereby saving time during the loan cycle.
Automation of Loan Assignment Process
The loan assignment process involves logging into LOS, manually review all the loan applications, and then allocate the loan applications to qualified user.
Loan assignment teams ensure a balanced allocation of loans. Post this, the team updates tracker to confirm assignment to users.
It is an extremely resource-intensive process and consumes time. The entire task can be automated based on a robust load balancing logic.
Mortgage process automation solutions like intelligent process automation (IPA) optimizes the entire process of ordering, obtaining, and verifying information of borrowers from third-party providers.
IPA can be programmed with preset business rules to automate the task of ordering and receiving data from third parties and then updating lenders’ own software system.
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Hyperautomation
Hyperautomation is a mortgage automation discipline. This cognitive automation discipline is a combination of machine learning and artificial intelligence algorithms, robotic process automation, and natural language processing.
It enables faster processing of loans. This framework can detect any anomalies in loan documents.
Hyperautomation involves using if AI-powered chatbots to enhance customer experience. It enters correct customer data into lenders’ LOS without any errors.
Conclusion
The market is teeming with mortgage process automation solutions engineered by prominent technology companies. However, it is essential that lenders choose automation solutions that are aligned with the ground reality of the mortgage industry rather than industry assumptions made by CTOs.
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