The wake of the housing crisis bore an avalanche of regulatory changes, which has resulted in soaring compliance risks and operational costs. Lenders are increasingly concerned about data integrity and quality control during the loan process, and this focus on data integrity has significantly increased total loan production costs. Given the increased costs associated with complying with ever-changing regulatory requirements, total loan production costs are not only soaring, but in many cases rising compliance costs have made loan origination unprofitable.
As today’s lending environment becomes more complex, traditional document management models pose a significant hurdle for maintaining quality control and controlling costs throughout the lifecycle of a loan. Also, legacy LOSs have failed to keep pace with the amount of automation required to cope with the rising cost of loan origination. Increasingly, lenders are being forced to reevaluate their operations to ensure that their document and data management operations have sufficient automation and adequate data integrity controls to satisfy compliance requirements without increasing costs.
As lenders increasingly turn to technology to automate much of the loan life cycle, they are in fact moving toward a straight-through processing (STP) model. The concepts of straight-through processing (STP) were originally developed to describe debt and equity trading and payment transactions that are conducted electronically without the need for re-keying data or manual intervention. Although the goal of “same day settlement” that the STP model promised equity trading has not been realized, the concepts of STP are applied in financial markets today to improve the certainty of settlement, minimize operational costs, and reduce systemic and operational risk. The mortgage industry can realize similar benefits, and others, by applying the concepts of STP to the loan origination process. When the STP model is applied to mortgage loan origination, much of the loan process is automated, resulting in up to an 80 percent reduction in labor. With STP, loan turn times are reduced, costly labor is eliminated and compliance is easily managed.
Today, many key steps in the loan lifecycle are labor-intensive and error-prone. The practice of “stare and compare,” for example, in which a human being looks back and forth across two or more documents to verify that the information is consistent across document types, is time-consuming and costly – and errors are common. Since the STP model reduces up to 80 percent of manual labor, human intervention is required only when something that is flagged by an automation engine needs to be validated. Using this exception-based processing model not only speeds the loan lifecycle, but also helps lenders better optimize the time of their most knowledgeable staff members.
As another example, loan data could be extracted and put through a rules engine to automate pre-funding and post-close quality control. Only if the loan application has a data point outside of the rules parameters would it then be sent to a human for review. This standardizes the process, increases productivity, lowers cost and minimizes quality risks.
Historically, it’s been feasible for lenders to send only a small percentage of loans through a quality control process, despite the growing pressure from regulatory oversight for more control and thoroughness. Typically, quality control is performed by in-house staff or an outsourced third party late in the origination process, or even after a loan closes. This drastically reduces the ability to take cost-effective corrective actions, and leaves the lender vulnerable to compliance risks. With the STP model, quality control moves to the front of the loan process and it becomes feasible to perform quality control for 100 percent of loans.
As the mortgage industry continues to evolve, and data integrity and quality control move front and center, lenders need to rethink the traditional ways of doing business. In the past, a focus on quality control meant increasing total loan production costs to the point of unprofitability and slower loan turn times. However, with the adoption of STP as a way of introducing quality control throughout the loan lifecycle, lenders are able to shorten loan turn times and ensure data integrity by using technology to automate most of the loan process. This not only reduces labor costs, but also eliminates compliance risks and buy backs that result from data integrity issues. In today’s competitive and regulated environment, adopting an STP model gives lenders a sustainable competitive advantage.
About The Author
With more than 17 years as Capsilon’s Founder and CEO, Sanjeev Malaney has proven himself as a visionary, a pioneer and a leader when it comes to the quest for transforming the mortgage industry. Capsilon builds intelligent tools that transform the way mortgage companies work. The Capsilon platform uses data and AI to radically improve workflows, automate manual tasks and enable smarter decision making at every step, boosting productivity across all mortgage functions. 15% of all mortgages in the U.S. touch Capsilon’s platform.