The loan manufacturing process, from application through post-closing to servicing and investor delivery, has traditionally been one in which the loan file flows through a relatively linear path. Unfortunately, this path travels through individual silos of various inefficient and, thus, costly operational processes.

While improvements in the functionality of loan origination software and servicing systems have done wonders to enhance those respective processes, often different teams manage the operational tasks which are executed in parallel. These operational steps, or lack thereof, can potentially compromise loan quality, exposing lenders to investor and regulatory compliance risks, loan salability issues, lower margins, and continued operational inefficiencies.

The critical component in achieving regulatory compliance, investor fulfillment, and borrower satisfaction is a complete and accurate loan record which still remains a challenge for many lenders. Are all documents in the loan file? Are the correct versions being used? Have documents been modified during the various stages of the manufacturing process? Is the data still accurate?

Determining the completeness of the loan file and the accuracy of the included documentation and data is critical to ensuring that a loan file can be successfully serviced and acted upon in accordance with investor, legal, and regulatory requirements. Furthermore, lenders must have the ability to have a consistent and seamless view of their risks throughout all stages of the loan life cycle, while the borrower is also entitled to quick access to their loan data and documents upon request.

Today, technology has been integrated together to successfully automate these processes, referred to here as the “loan completion process.” A successful implementation of an automated loan completion process, integrated with the origination and/or servicing system, will act as an operational technology enabler in assisting lenders with the ability to enhance lender process efficiency and borrower access while reducing investor and regulatory compliance risk.

EVOLVING PROCESSING REQUIREMENTS

Historically, traditional quality control processes involved numerous manual steps to review loan file documentation, data and to execute the operational aspects of the loan manufacturing process. Much of the process involved a physical review of the loan file — often a statistically relevant sampling — in a post-closing setting and a review of operational processes against an established QC plan. The loan file data itself resided in multiple systems such as a loan origination system, underwriting system, post-closing system, loan delivery system, image archive and other data repositories increasing the risk of inconsistent data, missing documentation and an incomplete loan record. The lack of a complete and accurate loan file has proven hazardous to investors and lenders  yielding regulatory enforcement consequences and potential repurchase risks.

To exacerbate the already risk-plagued historical loan manufacturing process, this year started off with the implementation of several new consumer laws that have had a significant impact on the lending community.

The introduction of the Qualified Mortgage rule, points and fee caps and other requirements that are enforced by the CFPB have dramatically impacted the loan manufacturing process.

On the investor front, Fannie Mae and Freddie Mac have taken great steps in helping lenders better understand the quality of their loan files. With the introduction of Fannie Mae’s EarlyCheck and Freddie Mac’s Loan Quality Advisor, lenders have the ability to review their loans against agency requirements and avoid costly defects associated with the loan manufacturing process.

In addition to increased regulation, the industry has seen a steady supply of mortgage servicing rights deals. MSRs have come up for bid from some of the largest lending institutions and have been a much needed source of revenue that has been successfully offsetting compressed margins and significantly reduced volumes on the origination side of the house. While many transactions are approved and closed, some have been blocked as a result of missing or erroneous documentation.

Potential MSR buyers need to properly conduct due diligence on any transaction and will require more detailed data extracts and imaged file samples prior to the transaction.

AUTOMATION TECHNOLOGY-BASED PROCESSING

Managing a quality loan asset throughout its lifecycle involves maintaining consistency throughout the capturing, processing and sharing of loan-related content. An automated loan completion process, managed effectively, helps to ensure both investor and regulatory compliance, reduces risk and improves operating efficiencies. Continual changes in regulatory oversight and investor requirements have introduced the use of multiple third-party stopgap solutions. These disparate and fragmented technology solutions can lead to efficiency declines, higher operating costs through, among other things, data transfer and reporting issues between loan origination, underwriting, post-closing, QC and servicing systems.

An end-to-end loan completion system should be able to successfully perform the following key basic functions:

• “Capture” data directly from loan asset, whether represented electronically or paper-based
• “Compare” the loan asset data against secondary source systems
• “Track” file actions and changes to data and documentation
• “Manage” individual operational tasks and workflows
• “Deliver” loan file data and documents to downstream systems and external constituents

Today’s data “capture” offerings have significantly advanced over previously attempted electronic capture technologies. For image-based files (such as Tiff formatted), the optical character recognition (OCR) engines of today have algorithms which have greatly improved the success rate of “reading” (turning imaged characters into machine readable text) image files. Most leading OCR engines perform this role quite well and should not be thought of in the context of previous OCR technologies.

Once in electronic form, typically either OCR’d Tiff images or indexed-based PDFs, document classification and data extraction routines can now be tuned to recognize hundreds of mortgage loan documents. Unlike the plethora of OCR engines available today, whose differentiator has become more concentrated on processing throughput than recognition accuracy, classification and extraction engines differ not in performance, but rather in the implementation of the rule sets used to achieve the classifications of the various mortgage loan documents.

Hence, once a superior capture technology is chosen to achieve automated indexing and full mortgage document classification, the benefit to the process is the assurance that the loan file is complete and the documents are accurate. Downstream investor repurchase risk resulting from missing documents is substantially mitigated. Compliance with Dodd-Frank requirements, such as verifying the borrower’s ability to repay, is evidenced via the complete documents in the file. The risk of MSR transfers being denied due to missing documents necessary to “final certify” a pool are eliminated.

The next major technology advancement for loan operational processing using a loan completion process is in ensuring the consistency of the data used in the numerous systems originating, consuming, analyzing, verifying, examining, sharing and utilizing the data that is continuously collected in the loan manufacturing process. As this data is collected, then distributed to multiple systems, changes to the data occur whether due to updating of expired data, adding additional data, or simple human error and the data in these systems becomes out of sync with the original data source.

As the number of data stores grows, the true “system” of record really becomes the physical loan record itself, the electronic image representation of the data extracted directly from that physical loan record. As such, it is this data that should be used to “compare” other secondary sources of this “same” data for compatibility and consistency.

With this data comparison method, discrepancies in downstream systems are avoided and accuracy of the loan record is maintained.

A necessary step and major longer-term benefit arising out of increased regulatory scrutiny is the increased focus on the electronic “tracking,” logging and storing of all changes to a loan record. A standard function of any automated loan completion system is to not only track the existence of specific critical documents, but any addition, update, modification or deletion of documents or data within the loan record. The long-term benefit of all this automated tracking is whether at the request of auditors, investors or as a prerequisite of insurers, having the log of any change to data in the loan record could prevent a lender from failing an audit or incurring the cost of buybacks.

Historically, quality checks focused mainly on a statistical sampling of loan files. With the loan completion system automating the data extraction and data source comparisons, quality checks can now be accomplished on virtually 100% of the electronic loan records. Although this provides for a higher percentage of accurate and complete loan records within the given portfolio, it does mean that exceptions in the loan records are discovered more often and much more quickly. Although there is an obvious benefit of 100% quality checking to the portfolio, it does have an impact on the operational workload. To combat any negative impact to processing time, a loan completion system needs to efficiently “manage” the assignment, presentment, processing and tracking workflow screens and actions that personnel need to use to manage the disposition of exceptions that ensure file and data accuracy.

Finally, the automation of the loan completion process brings lenders efficiency and speed to the “delivery” of the loan record. This automated process brings technology together to provide not only a mechanism to more easily adhere to the time sensitive nature of regulatory inspired deliverables, but also provide lenders a competitive advantage by bringing speed, accuracy and cost efficiency to the delivery of loan records to investors, insurers, and legal consumers of the delivered loan package.

In today’s greatly evolved investor and regulatory landscape, integrating this automated functionality into the loan manufacturing process while maintaining consistency throughout, has become essential. Lenders must ensure that their loan files are complete and the information contained in the file is accurate. Automating quality control functionality by leveraging the data contained in the loan file as well as in the internal systems of record will significantly mitigate the risk of noncompliance with investor and regulatory requirements. By better leveraging available technology, lenders can have a consistent and seamless view of their risks throughout all stages of the loan life cycle while simultaneously improving operating efficiencies and reducing expenses.