Using A Straight-Through Processing Model Can Boost Loan Quality And Reduce Origination Costs


Using A Straight-Through Processing Model Can Boost Loan Quality And Reduce Origination Costs BLOG VIEW: Since the bubble burst in 2008, the housing industry has seen close to 1,000 compliance changes from multiple agencies, with no end in sight. The Dodd-Frank-related regulations alone number more than 11,000 pages.

As lenders grapple with this new regulatory environment, data integrity and loan quality are moving to the top of the priority list. In fact, according to a survey Capsilon conducted during last year's Mortgage Bankers Association's (MBA) Annual Convention and Expo, 95% of the lending executives surveyed said they are either ‘very concerned’ or ‘somewhat concerned’ about loan quality, while 80% plan to spend ‘significantly more’ or ‘somewhat more’ on compliance-related activities this year versus what they spent on these activities in 2014.

This increase in spending on quality control and compliance has been a major factor in the run-up of personnel-related loan production expenses that, according to the MBA, are now routinely averaging more than $4,000 per loan, expenses that have increased dramatically over the past couple of years. And as loans are checked and re-checked to ensure compliance, loan turn times have suffered. In fact, according to the most recent Quarterly Mortgage Bankers Performance Report issued by the MBA, the average number of loans originated per production employee is just over two loans per month, a mere fraction of the double-digit productivity of production employees before the housing bubble burst. Not surprisingly, today's more complex environment is putting enormous pressure on lenders' profits.Â

As the complexity of loan origination increases, legacy loan origination systems (LOSs) cannot kept pace with the amount of automation required to cope with the rising costs of loan production. What's more, traditional document management models are falling short in maintaining quality control and controlling costs throughout the lifecycle of a loan. As a result, lenders are actively re-evaluating their entire 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 continue to struggle with how to ensure data integrity and loan quality without driving up total loan production expenses to the point of un-profitability, leading lenders are adopting technology, including data extraction capabilities, to move quality control forward in the loan origination process. And, leveraging technology, forward-thinking lenders are moving toward a straight-through processing model to dramatically reduce the amount of labor required at every step in the origination process, thus dramatically reducing loan turn times and total loan production costs.

The concepts of straight-through processing, commonly referred to as ‘STP,’ were originally developed to describe a complete trade process for capital market and payment transactions that is conducted electronically, without the need for manual intervention. Since originally conceived, the concepts of STP have been applied in financial markets to improve the certainty of settlement, minimize operational costs, and reduce operational risk. The mortgage industry can realize similar benefits, and others, by applying the concepts of STP to the loan origination process. The STP model automates much of the loan process, reduces manual intervention, and speeds processing while ensuring data integrity and loan quality.

When the STP model is applied to mortgage loan origination, manual labor is reduced by up to 80% and loan turn times are significantly reduced because the ‘multiple touches’ required today are all but eliminated. Under this model, human intervention is required only when something that is flagged by the automation engine needs to be validated.

For 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 contains a data point that falls outside of the rules parameters would it then be sent to a human for review.Â

Compared with the ‘stare and compare’ approach commonly used today, which relies on in-house staff or outsourced labor to visually compare data across multiple documents as a means of verifying loan information for accuracy and completeness and is costly, slow, and error-prone, this exception-based model standardizes the process, increases productivity, lowers cost, and minimizes quality risks.

And, it has the added benefit of optimizing the time of your most valuable employees. For example, an underwriter might only be involved to verify ‘exceptions,’ so she can spend her time where it's most valuable – underwriting more loans.

With today's hyper-focus on data integrity and quality control, lenders must rethink their entire operations. By adopting the concepts of straight-through processing to introduce quality control earlier in the loan lifecycle, lenders are able to leverage technology to automate key steps along the entire lifecycle, reducing manual labor by up to 80%, speeding loan turn times, and reducing total loan production costs. In today's highly competitive and regulated lending environment, adopting an STP model gives lenders a sustainable competitive advantage.

Sanjeev Malaney is founder and chief executive officer of Capsilon Corp., a provider of comprehensive cloud-based document imaging and data capture solutions that enable mortgage lenders and investors to increase productivity and lower costs, while ensuring compliance.

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