AI Based Textual Analysis vs. Other Approaches

Today there are many technology options available to assist in the automation of mortgage loan processing.  Some solutions are well marketed and low cost with great claims of vast libraries of rules and an ability to provide tremendous results.  There are even approaches which claim that OCR is an antiquated technology, but go on to either apply very low cost labor or other older technology approaches or a combination of these.  

Alternative Approaches

There are three typical methodologies applied to document classification. Below, we provide a high-level overview of each, along with some discussion of data extraction with each approach:

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Full Page OCR for Document Classification

This approach to document classification is distinct from most other classification technologies in that it uses a full-page OCR pass for every page of every document presented to it. Ideally, an entire page is read in less than half a second and then a set of rules are applied to determine which document type each page belongs to. While this would seem to be an obvious way to approach the task of identifying the very diverse documents found in the mortgage industry, most technology providers are unable to deliver the speed necessary to successfully scale with this approach.

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Advantages of this approach include:

>>Ability to index document versions which may have never been seen before by the system assuming they are lexically similar (same words and phrases found throughout)

>>Ability to accurately distinguish between leading pages and following pages, thus eliminating need to include separator sheets in the scanning process

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>>Ability to “discover” data for capture in a similar way to how a human being does it using words and phrases across the entire document to find key data.

>>High speed OCR allows for almost infinite scalability with a relatively small hardware footprint

Visual Classification also known as Fingerprinting

This is an old approach which has is been remarketed and renamed today by some vendors as AI for use in the mortgage industry.  While it does recognize and have the advantage of sub-second speed it is NOT an OCR solution.  Therefore instead, an image analysis (non-text based) approach is used to identify documents and page types. 

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This solution attempts to differentiate between document type A and document type B largely by examining the distribution of ink on samples of each document type. This is like a thumbprint analysis i.e. a graphical signature of each document type is learned and remembered.

The Advantage of this methodology include:

>>Performance (for the images successfully processed by the image signature method) 

Disadvantages of this methodology include:

>>The layout-specific configurations needed for each document variation can take a long time to set up if the number of document variations/types is high.

>>These layout-specific configurations need to change if the layout of a document ever changes.

>>The graphical signature approach tends to be less reliable with more than one hundred document variations/types to compare. This can affect accuracy in some cases.

>>The time to process images tends to be linearly related to the number of document variations/types.

>>This approach presents challenges when attempting to detect document boundaries for multiple page documents and does not provide an ability to extract data from the documents once identified.

Dynamic Learning

This approach does NOT have the advantage of a sub-second OCR solution but it does use OCR as part of its document classification and data extraction methodology to enhance its results.  In general, the system is a mix of preconfigured rules, a learned knowledgebase and layout-specific configurations. The rules are configured through a GUI but more complex operations require scripting. The technology is typically configured for mailroom and Accounts Payable environments.

Learning is achieved by running real production data through the system to a human verification step. The system attempts to learn from the document classification and data extraction decisions made by the verification operator.

An advantage of this technology is: In-production learning allows rapid use of layout specific information. Unfortunately, this advantage is also a disadvantage. Many higher-volume sites require regression testing prior to promotion of any configuration change into production. This methodology is based on a belief that this is not necessary. 

Other disadvantages include:

>>As the system adds layout-specific templates, the system gets proportionately slower

>>Separator sheets between multi-page documents are required

>>Production errors occur if layouts change

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AI-Based Textual Analysis

In today’s mortgage market you can’t pick up an industry publication or attend a trade show and not hear someone talk about Artificial Intelligence (AI).  Many of the claims talk about how AI will disrupt the mortgage industry or radically change how mortgages are originated or processed.

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Some of it is pure hype and some of it includes technology that can clearly streamline processes and reduce cost.  So how do you filter fact from fiction?  Let’s take a look at how AI-based textual analysis is actually at work in the mortgage industry and the different approaches some vendors are using.

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High-Level Approach

The most fundamental difference in approach between an AI textual analysis and the majority of other “advanced” document recognition technologies is that AI textual analysis treats variable layout documents as unstructured documents whereas most other prominent solutions treat them more as semi-structured documents.

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To illustrate the difference in methodology let us consider a customer wishing to process pay stub documents. An AI textual analysis implementation would typically be deployed with one set of completely generic rules designed to encompass all variations of the “Pay Stub” document type from any company.  Because alltext is evaluated by the AI engine, the rules can flex with the layout and verbiage changes just as a human does when reading the page. The solution is also capable of being configured to perform conditional processing for specific exceptions to generic rules (per-layout exceptions) but it is not typically necessary to do this.

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Most other modern advanced document recognition technologies treat document variations as semi-structured documents. These solutions typically either: 

a) Remember as many of the variations as is practical and process each variation with layout-specific templates for processing Or b) Apply a mix of layout-specific processing and some generic processing (usually the higher incidence layouts are processed with layout-specific or templated processing) 

The obvious advantage of the AI textual analysis generic approach is that, as new layouts appear or existing layouts change, the software is better equipped to deal with these new variations. This advantage was recently validated at an account with over 35,000 layout variations where rules had been in place for five years with not a single modification. An audit of this client’s processes after five years revealed an identical automation rate to that when the system was first deployed. This outcome was observed despite the fact that a significant portion of the originally dominant layouts had been transferred to EDI processingand were therefore bypassing the system now. 

As you can see the varying approaches often produce different levels of success.  But how can you determine which is best for your organization? Get a demo and hope that the solution is more than smoke and mirrors?  Up until now that is usually the case.  To overcome much of the confusion and disappointment, a better evaluation process in many cases may go a long way towards greatly minimizing the risks involved in choosing a vendor who can actually deliver AI-based textual analysis.

In order to quickly understand AI-based textual analysis and its capabilities, a blind test with several sample files should be considered the gold standard for an evaluation.  This is especially true when it comes to the challenges presented with the many and varying document types and quality levels of document images found in the mortgage industry.  Asking vendors if they are willing to perform a test on a never before seen sample set of typical loan files on site and in sight of your evaluation team, is a great first step in separating fact from fiction.

Ideally, an evaluation should be setup as a one day event to hedge against any vendor refining their results.  This kind of test is intended to demonstrate the validity of the vendors’ out-of-the-box capabilities so that prospects can be assured that they are considering a proven, robust and scalable solution ready to deliver productivity improvements in weeks rather than months or years.

For qualified opportunities, Paradatec will perform this process, which enables prospective clients to quickly understand the overall levels of automation, and speed improvements they will be able to achieve with their technology.  Download our whitepaper on AI based textual analysis

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Evaluating An OCR Solution for Mortgage Documents

Today there are many OCR technology options available to assist in the automation of mortgage loan processing.  Some solutions are well marketed and low cost with great claims of vast libraries of rules and an ability to provide tremendous results. Unfortunately, the reality is that OCR technology users and prospects are often disappointed in the results of current and past OCR evaluations and initiatives.  So, they’re understandably cautious and untrusting. To overcome much of the confusion and disappointment, a better evaluation process in many cases may go a long way towards greatly minimizing the risks involved in choosing an OCR technology vendor.

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In order to quickly understand an OCR technology and its capabilities, a blind test with several sample files should be considered the gold standard for an evaluation.  This is especially true when it comes to the challenges presented with the many and varying document types and quality levels of document images found in the mortgage industry.  Asking vendors if they are willing to perform a test on a never before seen sample set of typical loan files on siteand in sightof your evaluation team, is a good first step in shortening your list of viable vendors for your project.

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The test is often conducted on-site, rather than at a vendor’s facilities, due in part to the typically confidential nature of the content, but to also minimize concerns about the possible skewing of any results behind the scenes.  Look for a pre-built mortgage OCR library which can offer clients a short evaluation and implementation timeline rather than a requirement to develop processes and rules from the ground up.  Ideally, an evaluation should be setup as a One-Day Blind Test.  This kind of test is intended to demonstrate the validity of vendor claims so that prospects can be assured that they are considering a proven, robust and scalable solution ready to deliver productivity improvements in weeks rather than months or years.

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In the course of a One-Day Blind Test, provided loan files should be indexed by document type and 50-100 data fields should be extracted from various key documents like the Note, Deed of Trust, Closing Disclosure, and Appraisal.  Output results should be provided along with statistical reporting describing automation and processing times.

Unfortunately, many companies base their buying decision primarily on price, only to be disappointed with the lack of true out-of-the box mortgage-specific functionality offered by the product.  In other cases, great claims are made regarding OCR automation, with the reality being something less impressive.  

For qualified opportunities, Paradatec has been performing this process which enables prospective clients to quickly understand the overall levels of automation and speed improvements they will be able to achieve with their technology.  Paradatec calls their evaluation the One-Day Blind Test Challenge.  

Paradatec’s Advanced OCR solutions offer significant efficiencies for classifying large quantities of differing document types and extracting key data elements from those documents.  In the mortgage market, these capabilities allow for the quick and accurate identification of over 500 unique documents in the typical mortgage file, along with capturing nearly any data element from those documents that an organization requires.  For more information, please visit

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Looking At OCR Use Cases In Mortgage Lending

With the costs to process each mortgage continuing to rise, lenders must leverage automation to improve profitability and consistency in their business processes.  With the right Advanced Mortgage OCR solution, mortgage companies have been able to reduce their level of manual document indexing and data entry activity, enabling them to process more loans per day at a lower cost per loan – yielding a leaner process and increased profit margins. 

Advanced OCR, More Than Just Reading Characters

An Advanced Mortgage OCR solution needs to do more than just convert document images to text.  Once converted, an advanced OCR solution should then be able to interpret that text using Semantic Analysis and artificial intelligence (“AI”) rules engines in a similar way a human being would process the content. Based on these results, documents can be automatically indexed and relevant datapoints extracted.  This information is then passed to downstream applications for appropriate routing, and archival. 

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A Technology Vendor with a Unique Approach

For today’s most advanced OCR solution, the OCR process begins with a full-page OCR scan of each image.  This step is unique and typically completed in less than one second per page.  An extremely high-speed OCR process is critical and yet difficult for many vendors to achieve.  It is this performance, which allows every word on the page to be included in the scope of the AI rules engine analysis, just as a human being would interpret the content.  This content evaluation process is unique in terms of the combination of speed and ability to include allpage content in the evaluation scope, thereby making it extremely flexible with documents of varying layout (for example, bank statements).  

OCR in Action Use Cases from Leading Lenders

>>TRID Capture and Audit

The ideal OCR solution provides a rigorous tool for a comprehensive review of each TRID transaction. Typically, during the origination process there are several iterations of both a Loan Estimate and a Closing Disclosure. The most efficient TRID Audit solution is able to extract every data element from all initial and re-disclosed Loan Estimates and Closing Disclosures. The system can be configured to either output all of the data from each document iteration, or output just the differences found from the prior document. Output formats should include MISMO v3.3 or custom XML schemas. 

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In the case where a loan origination system is generating the TRID disclosures, this differential reporting may be something produced by the LOS itself. However, in the correspondent lending channel, or in the case of a split, “borrower-only” and “seller-only” Closing Disclosure transaction, this Advanced OCR solution closes a gap that the LOS is unable to address. 

In these cases where the lender’s LOS does not generate all iterations of the Closing Disclosure and Loan Estimate, a solution is needed that can natively read PDF or scanned TIFF versions of these documents. This type of TRID Audit solution has been developed and tested to support any layout of these documents from any source.

>>UCD Creation and Audit

The Uniform Closing Dataset (UCD) provides a common industry dataset to support the Consumer Financial Protection Bureau’s (CFPB) Closing Disclosure and its ability to be communicated electronically. 

Loans closed on or after September 25, 2017 which are acquired by the  GSEs are required to have both a UCD XML file and after June 25, 2018 an embedded PDF of the associated Borrower Closing Disclosure. 

Over time the UCD is intended to provide the following benefits:

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A. Greater data consistency by promoting better and more efficient data integration and exchange between business partners.

B. A common understanding, as all parties use a consistent approach and language to describe the information on the Closing Disclosure.

C. Improved data accuracy by eliminating the need for proprietary formats that can be costly to maintain and can lead to misinterpretation of the data.

The GSEs are collecting UCD data because it:

A. Helps enhance credit risk management with more data and better quality data.

B. Provides important information to help increase their ability to detect fraud and misrepresentation at loan delivery.

C. Provides additional transparency into the mortgage loan transaction file to help assess whether the loan, as closed, meets the GSE’s eligibility requirements.

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According to the GSEs a PDF of the Closing Disclosure needs to be embedded in the UCD because, “The Borrower Closing Disclosure is the definitive record of the fees, charges, and adjustments that occurred in the loan transaction. As such, it is used to validate that the information provided in the UCD submission is complete and accurate.”

July 2018 UPDATE: As the new requirement for embedding a PDF of the Borrower’s Closing Disclosure was beginning to rollout, leading solution providers engineered a solution to perform an audit to statistically measure the accuracy between the data found on the embedded PDF and the MISMO XML data found in the UCD.  

The right solution provides the tools to determine if the data on the embedded PDF Closing Disclosure source document actually matches the same data within the UCD XML file. While this capability is certainly valuable to GSE entities, it is also possible to use this audit for other loan transfers.  As part of a due diligence process, investors may use this capability to verify that a set of loans to be purchased is as advertised and all critical metadata provided is accurate.

>>HMDA Audit

In order to promote compliance with federal consumer protection laws, lenders are required to submit certain borrower demographic data to the federal government. HMDA (Home Mortgage Disclosure Act) disclosures provide the public with information on the home mortgage lending activities of most lenders.

One of the challenges for a lender in reporting HMDA data is to ensure that the documents from which data is pulled are, in fact, the final versions. Many times errors in HMDA reporting are due to reporting data based on a non-final source document.

The most advanced OCR solution for HMDA Audits searches through an image archive for every version of every document relevant to the HMDA reporting process and automatically determines the final versions. Data is then automatically captured from these final documents via their AI data extraction rules and coalesced into an XML file or spreadsheet to be used for reporting. 

This process provides lenders with a highly automated method for assuring accuracy of required Loan Application Register (LAR) reporting data and to ensure database of record quality for future reporting needs.

What’s New in 2018?

>>OnDemand OCR capture (W2s, Paystubs, and Tax forms)

As the industry continues to look for faster and more efficient ways to capture key data from prospective borrowers, a leading OCR provider has been listening.  Their sub-second speed OCR is the ideal technology platform from which to allow borrowers, loan officers and others to submit supporting loan documentation for quick automated document identification and data field capture.

A user may drag a PDF of their Federal IRS 1040 Income Tax form to a browser-based app, the form will be identified and all data fields captured in a short time frame and immediately available to loan officers and loan origination systems.

>>Necessary but Unique Capabilities

The key capabilities and features of the Paradatec Advanced OCR solution that make these use cases possible are:

A. Sub-second per image full OCR processing

Paradatec advanced indexing and data capture technology is at least 10 times faster than others, which allows them to take an approach others would like to, but just can’t because of their system performance. This capability is unique, and enables Paradatec to evaluate all text on every page, just as a human can but much faster. 

B. Extreme scalability with a small hardware footprint 

Paradatec’s Advanced OCR solution scales from the ability to process over 1,000,000 images daily on a single eight core server to tens of millions of images daily by simply enlisting additional cores into the configuration.

C. Pre-built mortgage OCR library

Over 500 mortgage document types ready to be indexed, and more than 6,000 mortgage loan data fields able to be captured right “out of the box”.  

D. Web services API

Paradatec’s OnDemand OCR feature extends their Advanced OCR capabilities to other applications through seamless integration with a web services API.

E. Document versioning

Documents can be stacked, with like documents consolidated together, to streamline the document versioning process.

F. Bookmarked PDF output

Paradatec’s WritePDF module provides a bookmarked and annotated PDF of the submitted loan package, including a table of contents with links to key data elements within the package.  Clients find this feature invaluable and a significant documentation addition to their inventories of mortgage loans.

Paradatec’s Advanced Mortgage OCR solutionis designed to make mortgage lending faster and more accurate.   In 2017, Paradatec’s Mortgage OCR solution processed over 1,500,000,000 images (representing over 2,500,000 loans), helping lenders and servicers streamline their origination, onboarding and compliance obligations by automating document indexing, automating data extraction, meeting tighter service level agreements, and delivering more accurate data much faster than manual data entry alone. In 2018, Paradatec is on track to again exceed the volumes processed and the automation provided to their lender, servicer, and other technology provider clients in the mortgage lending industry.

About The Author

Tackling Industry Innovation

The PROGRESS in Lending Innovations Award Winners gathered to talk about the future of mortgage lending. Over 100 mortgage executives came together to attend PROGRESS in Lending Association’s Eighth Annual Innovations Awards Event. We named the top innovations of the past twelve months. After that event, we wondered what would happen if we brought together executives from the winning companies to talk about mortgage technology innovation. Where do they see the state of industry innovation right now? And what innovation is it going to take to get our industry really going strong? To get these and other questions answered, we got the winning group together. In the end, here’s what they said:

Q: Some say innovation has to be sweeping change. Others say innovation can be incremental change. How would you define innovation?

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MICHAEL KOLBRENER: At PromonTech we are very careful with the word “innovation”. While we strive to be innovative, whether or not we succeed isn’t our call, but our clients’ and the market’s. At the end of the day, innovation is in the eyes of the user. And innovation can manifest itself differently; it can be a “big bang” like Apple’s iPhone, or it can occur more gradually and quietly like Internet availability. Fannie Mae and FormFree are great examples in our industry of how significant technology opportunities require time in order to be realized. Day 1 Certainty is destined to be a game-changer, but adoption may take time. Just like it took time for the amazing tools in FNMA Desktop Underwriter to be appreciated. As technologists, it’s our job to celebrate the important technology opportunities and help our user communities keep working on adoption.

JOHN PAASONEN: Innovation, especially in our industry, takes many forms. Innovation pushes forward a process, changes a mentality, or reforms the way something is thought about or done. We’re seeing all forms of this in mortgage, whether it is Day 1 Certainty, upfront underwriting, or shared-equity financing. The best kind of commercial innovation sweeps people along with the change in the present, not 10 years from now, bringing actionable ideas to market quickly, iterating those ideas, and ultimately delivering meaningful impact to the experience, P&L or relationships in a business.

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PHIL RASORI: Traditionally, I would say that innovation in our industry has been more of a gradual, step-by-step approach with new products, services and enhancements being launched as vendors identified demand and areas for improvement.  However, the introduction digital mortgage movement, which has been rapidly building over the past few years has been sweeping, with an array of fintechs and new ideas being spawned to build a better overall lending process. The trick now is going to be the rate of borrower and marketplace adoption of these new technologies.  Think about this: even adoption of now comfortable mainstays such as online shopping with Amazon or online trading with Schwab didn’t happen overnight. Adoption took time, and it will in the mortgage space, too.

GARTH GRAHAM: At STRATMOR, we see the innovation as a combination of People, Process and Technology, a variation on the classic 3Ps of People, Process and Product. You can have innovation that applies to any of the three, but it’s best is when it’s applied to all three together.  In fact, that was a key message in my presentation at the most recent MBA Technology Conference — that changing across people, process and technology is what drives big changes.

SANJEEV MALANEY: I would describe innovation as significant positive change resulting from fresh thinking that creates value for its user. It’s a result. It’s an outcome. It’s something one works toward. There are no qualifiers for how groundbreaking or world-shattering that something needs to be, only that it needs to be better than it was before. Innovation is evolutionary, not revolutionary — like Einstein’s theory of relativity.

KELCEY T. BROWN: At WebMax, we believe that innovation means identifying a problem and coming up with a unique solution. Whether it be sweeping or incremental, that unique solution changes things for the better. Innovation, especially in mortgage technology, has been defined by streamlining processes, reducing operating and origination costs, and delivering a better borrowing experience.

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ADAM BATAYEH: For us, it’s all about progress. Almost any amount of progress will do no matter how incremental the change is. If you create something that is cool and trendy but doesn’t necessarily push things forward in a way that betters people/process/industry, that “innovation” was more novelty than anything and will likely find itself extinct.

So in terms of impact, the amount of impact/progress isn’t as important because of all that happens downstream that we may not see immediately. You could make an incremental change that has monumental implications years later. In our space, it’s sort of like the butterfly effect.

LUKE WIMER: Innovation is the achievement of a consistently better outcome for time invested in an activity. I think creative problem solving needs to be encouraged, so we need to think of it as incremental change, and then allow for sweeping change to be the aggregation of persistent innovation. In our industry context, we might refer to the ability to electronically sign a mortgage as an innovation and the ability to digitally process a mortgage end-to-end as the sweeping change we are all driving toward.  Innovation is also often the result of fostering a culture of continuous improvement. In our company, we set long-term aspirations, then we ask everyone to set improvement or innovation goals for the next quarter or half year. We don’t specify how to improve; we don’t want people to be constrained. Then we measure results, talk about what happened, and set goals for the next round, rewarding examination and striving rather than hitting the target itself. The pace of creativity is increasing as people get comfortable taking risks.

NEIL FRASER: Innovation, in most cases brings incremental change. Over time many incremental changes bring about what can appear to be sudden sweeping change. As the mortgage industry moves towards the sweeping change being called the Digital Mortgage, many innovations have been, and continue to be tried and tested. This is the necessary process for moving an entire industry towards a significantly different model.

At Paradatec, we are continuing to innovate in an effort to support the industry’s long term move towards a more efficient and accurate process for originating, servicing, and auditing mortgage loans.

More specifically, we define innovation in our particular niche as “the application of artificial intelligence to the problem of document recognition”. This could mean the creation of a new, more automated, document classification solution for a servicing world where scanned images of documents, that were originally paper, are still key, or it could mean the creation of new recognition capabilities for e-signed documents that never were paper. Regardless of the application, we at Paradatec are committed to an ever-expanding document recognition stack that covers origination, servicing and auditing mortgage loans.

Q: How would you define the state of innovation in the mortgage industry? Is it thriving or in a state of decay?

MICHAEL KOLBRENER: The mortgage industry is in an unprecedented phase of technology adoption. There is no doubt that Rocket Mortgage deserves lots of credit for truly introducing the “Internet” to the mortgage industry. Rocket has shown all lenders that technology is an integral part of the future of mortgage originations. Additionally, we are seeing lots of new technology companies competing in the mortgage space (including PromonTech!) We’re just beginning to realize the many opportunities to improve efficiencies.

JOHN PAASONEN: Twenty four months ago, my answer may have been different. But today, it is a thrill and a privilege to participate in the transformation occuring in the mortgage industry. For nearly a decade — in the wake of the financial crisis, the passage of Dodd-Frank, the creation of the CFPB, and major regulation like TRID — investment dollars were poured into compliance, not advancement. I’m incredibly encouraged by the increasing openness to the work of many innovators, from both inside and outside the industry, to incite progress. Innovation is alive and needs to be spurred forward.

PHIL RASORI: Post the mortgage crash and subsequent introduction of a myriad of new rules and changing regulations with Dodd-Frank and enforcement by the CFPB became a huge concern and instantly drew everyone’s attention to compliance adherence, which arguably distracted from technology innovation. Now more than ever, the mortgage industry is on a fast-track to achieve far-reaching changes via new technology, which is being fueled by anticipated demand for borrower automation and lenders’ positioning themselves to remain competitive, thus driving innovation across the board. We’re not only thriving right now, but some say we’re drinking from a firehouse. Again, adoption will be key to these innovations becoming reality.

SANJEEV MALANEY: The industry is ready for innovation and we’re starting to see major transformation impacting the end-to-end mortgage process. New companies are flush with venture capital. Lenders are funding innovation centers using their own capital investments. People from outside the industry with diverse sets of skills and experience are being hired to drive this transformation. We’re going to see more innovation in the next twelve months than we’ve seen in years.

KELCEY T. BROWN: Innovation in the mortgage industry is thriving thanks to the continuous flow of new ideas and products, and growing interest in technology from lenders. We’re seeing point-of-sale products become more intuitive and borrower-friendly, and financial data retrievers’ rules engines making loan processing faster and more efficient. Lenders’ interest in digital mortgages continues to grow as today’s home buyers lean more and more toward a digital borrowing experience. That said, a great deal of the industry still needs to transition to digital mortgages. Growing interest, paired with a sizable unaddressed market, makes a perfect storm for thriving innovation.

As much blame is put on regulation for technical stagnation, we like to thank it. It put our backs against the wall and forced companies to make major changes that they couldn’t handle or weren’t willing to take on. It led to that consolidation, and most importantly, it led to massive amounts of investment in what we like to call “foundation over feature” and that has helped increase transparency, accountability, and more. It’s what laid the groundwork for all the innovation you are seeing today.

ADAM BATAYEH: Innovation is thriving, thriving, thriving. If this were 2013, the answer would have been massive decay. The thing is, that decay was necessary and led to all of the innovation we are seeing today.

LUKE WIMER: Mortgage is a bit late to the innovation party compared to payments or online banking, so we are still more focused on automation and efficiency and just starting to affect true change to the consumer experience.  But we should not underestimate the potential for change and innovation. The industry has been gearing up over the years with steps toward digitization, creative partnerships, driving new standards, and these will allow a fast pace of change once the scale is tipped. I am thinking of how one of Hemingway’s characters went bankrupt: “Gradually, then suddenly.”

NEIL FRASER: Innovation in the mortgage industry is definitely thriving today. For the last twelve years, we at Paradatec have focused on building our mortgage technology through advanced OCR using artificial intelligence and an ability to learn over time and provide increasingly more significant innovations.

In the last twelve years, we have not only increased our ability to innovate, but have further greatly accelerated this ability to innovate from our partnerships and integrations with others in the industry. This is a trend we expect to continue for years to come.

GARTH GRAHAM: I think that innovation is truly accelerating, but too often people define innovation as simply technology. They think the next software product, the next shiny object will transform their business. At STRATMOR, we often see companies with good people and good process being able to overcome substandard technology, but rarely do we see a company with great technology that can overcome poor people or process. This does not mean tech is not important, in fact I believe that we don’t spend enough on technology — but if you don’t have the people and process lined up to implement change, then the technology alone will not drive the results you seek.

Q: Lastly, if there was one innovation that you would say the mortgage industry desperately needs to happen over the next twelve months, what would it be?

MICHAEL KOLBRENER: All of us, in lending, need to evangelize the potential of technology and encourage our user audiences to understand the role it can play in the future of originations. Over the next 12 months, we need to keep pushing data providers to make applicant data more readily available, particularly around income verification (and tax supporting docs). At PromonTech that’s where we believe that next big breakthroughs will come.

JOHN PAASONEN: We’re just beginning to see the early signs of moving beyond “digital paper.” Over the last 10 years, the mortgage industry has largely taken a paper-bound process and digitized it. A loan application acted much like its paper counterpart, just with the ability to type answers, for example. In the next 12 months, regulators, lenders, investors and innovators need to continue to push forward with initiatives to all-together remove the tremendous burden on borrowers, loan officers, processors, appraisers and others created by our legacy of paper-driven process. The winners will be those who realize first that data availability and fidelity is too rich, and computing power too strong, to be ignored.

SANJEEV MALANEY: While we have witnessed significant innovation over the past year, there remains a series of key friction points that must be addressed for the mortgage process to truly be reinvented.

Perhaps the most critical enabler in our space (not unlike other verticals) is the use of data, and by extension, how to extract insights from that data to make faster and better decisions, which is where Capsilon is focusing its innovation efforts. It is worth noting, however, that while “big data analytics” has suddenly become a go-to catchphrase for many in our industry, our own experience in the space suggests that the challenges associated with implementing and realizing value from big data are more subtle.

For the past 14 years, we’ve been helping clients collect, validate and leverage the data to drive automation and improve productivity in the mortgage process. Those who succeed will master the harvesting and delivery of relevant data at the right time so every user (borrowers, LOs, underwriters, processors, closers) in the loan process are provided the information and tools they need when, where, and how they need it to remove friction in the loan process.

KELCEY T. BROWN: Faster adoption of digital mortgages. The faster lenders adopt digital mortgages, the better off their business will be, from their balance sheet to borrower satisfaction. It is evident that through technology, lenders can close loans faster, with more efficiency, for a better cost. At the same time, that boosted efficiency means borrowers get in their homes faster and are more satisfied with their mortgage experience. Real estate agent satisfaction grows as their listings get filled and closed faster as well, which can boost referrals. Imagine that your company waited to adopt email, how would that have worked out?

ADAM BATAYEH: To use our internal phrase again: foundation over feature. It seems that everyone is racing to be first with the next big thing and it’s very tempting to follow trends. At the same time, it can confuse lenders and can make it harder on them to make a decision. We can create all the new features we want, but if they’re hard to integrate and implement, we’ll find ourselves pigeonholed.

An example I can give is Windows vs. Mac OS and their respective web-browsers. The Operating System was the “foundation” and the web-browsers were built as “features”. Buy the OS, get the browser for free. The browser would work flawlessly with its respective OS.

Google Chrome came out of nowhere as it’s “foundation vs. feature” priority was the reverse. Knowing the future was in the Cloud, they built an agnostic browser, which resulted in Windows and Mac users collaborating in a new way. As Microsoft and Apple built browsers that were feature-focused and complimented their foundational Operating Systems, Google was busy playing the agnostic game and with Chrome has quickly emerged as the leader.

LUKE WIMER: There are so many different needs. I would like to see clarity on where federal regulators are headed. I would like to see some of this mortgage application automation technology make its way further into the loan origination process. We appreciate the need for increased security and rigor in vendor management, and are pushing for increased acceptance of SaaS and the tools many of us are making available to offer plug-in solutions. I believe it will be a collection of innovation and providers, which will be needed to really transform. It is a resilient sector that rolls with the punches, and is complex enough that no single innovation will win or solve the problems of every player. Therefore I am glad there are many of us working on improvement from different angles.

NEIL FRASER: Accurate data which reflects the terms, borrower, lender, and property information from Mortgage loans’ source documents will continue to be a critically important requirement. As a result, there will continue to be a need to audit the accuracy of the data as it relates to the legally definitive required source documents. As loans and their servicing rights are passed from investor to investor and servicer to servicer, a more efficient process for efficiently and accurately onboarding these loans as these transactions occur is desperately needed. At Paradatec, we are continuing to innovate and this need is one of major focus for us in the coming year.

GARTH GRAHAM: So, there certainly has been a significant amount of technology innovation at the point of sale — dynamic applications are more commonplace.  I think it’s what occurs BEFORE the application that is critical for the next year.  The reason is that we are pivoting to a heavy purchase market — only 25 percent refinance — down from roughly 50 percent refinance (or more) for the past 20 years.  This is a MAJOR difference and will really stress originators who are not equipped to handle purchase opportunities.  At STRATMOR we have a methodology of creating a digital roadmap for lenders, and we often find that they are not adequately valuing the tools that are required prior to application. We refer this to Lead Engagement — the ability to interact with purchase consumers across multiple touch points and for longer periods of time.   We also feel that price competition will become more acute going forward.  Thus, we think innovation needs to tackle the functions that typically are considered CRM functionality — managing customer interactions over long periods of time — as well as presentation to clearly show what customers are going to pay for their mortgages.

Also, we think that there is going to be a lot of industry consolidation, both for mortgage origination companies and for the technology vendors that support the lenders it.  At STRATMOR we are active in M&A and have never been busier with lenders looking for strategic alternatives, and with buyers who are well positioned for the future, and are actively looking to acquire other entities to gain market share during this difficult period.  Vendors are finding a similar climate, and some smaller vendors are seeking capital partners. New capital is entering the market to acquire additional technology capabilities.

PHIL RASORI: I hate to use what many feel is an over-used term these days, but acceptance of the “digital mortgage” and what it encompasses will be key to much of what is to follow. We are seeing that successfully be streamlined right now at the point-of-sale for borrowers. Digitization of the secondary market is also picking up speed, which is what we at MCT have been focused on. Technology integrations are essential for lenders to keep systems operating in real-time, while automation is streamlining processes. Digital whole loan trading is revolutionizing the loan sale process. Embracing the digital mortgage at every step in the process is helping lenders to increase efficiency and profits.

How Digital Can Drive Down Costs

In this era where smartphone and tablet usage permeates nearly all of life, it only seems logical that the purchase of a home would eventually move in the digital direction as well. This certainly creates a situation where the loan package can be digitally moved with minimal cost rather than printed (multiple times, most likely) and physically moved between geographies. Therefore, processing delays associated with in-transit time and cost can be reduced, improving the overall process for both lender and borrower.

However, while borrowers may be able to upload copies of their paystubs and bank statements for example, the data must still be gleaned from those documents as part of the underwriting process. Without the aid of sophisticated OCR, that gleaning process remains a manual process, even though the mortgage is “digital”.

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With the costs to process each mortgage continuing to rise, lenders must leverage automation to improve profitability and consistency in their business processes. With advanced mortgage OCR solutions, mortgage companies will reduce their level of manual document indexing and data entry activity, enabling them to process more loans per day at a lower cost per loan – yielding a leaner process and increased profit margins.

Paradatec’s Advanced Mortgage OCR solution does more than just convert document images to text. Once converted, that text is then processed by our artificial intelligence (“AI”) rules engine in the same way a human being would process the content. Based on these rules, documents are automatically indexed and relevant data points are extracted. This information is then passed to downstream applications for appropriate routing, decisioning, and archival.

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Our process begins with a full-page OCR scan of each image, typically completed in less than one second per page. This high-speed performance allows every word on the page to be included in the scope of the AI rules engine analysis, just as a human being would interpret the content. This content evaluation process is unique to Paradatec in terms of the combination of speed and ability to include all page content in the evaluation scope, thereby making it extremely flexible with documents of varying layout (for example, bank statements).

Other OCR solutions typically expect relevant data points to consistently appear in the same locations (or ‘zones’) on a document. If the data shifts due to changes in layout (again, think of bank statements), the zone-based approach will fail unless another layout template is created, making for a greater administrative burden with these solutions.

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A high volume, scalable OCR automation initiative requires the flexibility of Paradatec’s Advanced Mortgage OCR solution to process an unlimited number of document layouts without needing to develop specific templates for each layout variation. This capability is unique to Paradatec and a vital feature for creating an effective unstructured document classification and data capture solution.

Applying the right technology in the digital lending world can drive down cost providing lenders with a significant competitive advantage.

About The Author

And The 2018 Winners Are …

Prominent mortgage executives gathered to see who the Executive Team of PROGRESS in Lending named the top industry innovations of the past year at the Eighth Annual Innovations Awards Event. This honor is the Gold Seal when it comes to recognizing true industry innovation. All applications were scored on a weighted scale. We looked for the innovation’s overall industry significance, the originality of the innovation, the positive change the innovation made possible, the intangible efficiencies gained as a result of the innovation, and the hard cost and time savings that the innovation enables industry participants to achieve. The top innovations winners are:


PROGRESS in Lending has named Lodasoft a top industry innovation. To address the CFPB requirements of improving the borrower experience, the first big wave of innovation has come out of Silicon Valley. Hundreds of millions of dollars have been invested in the consumer facing aspect of the borrower application. The term “digital mortgage” has been coined and a flood of shinny new mortgage websites and apps have been created to deliver borrowers an Amazon type borrower experience. However, the majority of dollars invested, have focused almost solely on the online application for borrowers. The problem is that mortgage lending is significantly more complicated than just a shinny new app. The right digital mortgage platform helps to drastically reduce the chaos in daily lending processes while improving communication to help lenders close more loans faster. Therefore, in 2017 Lodasoft introduced its truly innovative “Digital Mortgage Platform” featuring Intelligent Loan Manufacturing to address these industry challenges head on.


PROGRESS in Lending has named Capsilon a top industry innovation. A truly innovative mortgage process means more than borrower-friendly loan selection and document submission, it is an end-to-end solution that keeps all stakeholders in the loop throughout the process. In 2017, Capsilon introduced Point of Sale Portals (POS), enabling the creation and delivery of quality loan packages that streamline every process step from application to closing. Capsilon’s POS Portals are powered by Intelligent Process Automation to supercharge loan production from intake to delivery of complete and compliant loan packages. This is an industry first, dramatically improving loan quality and speed, while drastically reducing production costs. Lenders are pressed to meet the challenges of production, compliance and profitability, as well as soaring borrower expectations. Instead of simply streamlining the traditional loan process, in 2017, Capsilon launched Point of Sale Portals that are fully integrated with its patented back-end technology to deliver on the promise of a true digital mortgage.


PROGRESS in Lending has named WebMax a top industry innovation. According to Inc. Magazine, Millennials make up 66% of first-time homebuyers and 66% of them plan to buy a home in the next 5 years. Moreover, the same report found that Millennials associate home ownership with the American Dream more than any other generational demographic. The October 2017 composite forecast of Fannie Mae, Freddie Mac, and the Mortgage Bankers Association for 2017 mortgage origination volume is approximately $1.8 trillion. If Millennials compose 50% of this mortgage volume, and two-thirds of them apply online via digital applications, that represents $600 billion in digital mortgage origination. This number is massive. Better yet, it’s conservative. Millennials expect mobile-responsive mortgage lending sites and applications with a responsive layout from their potential lender. They want their mortgage application to be as easy as buying a t-shirt from an online retailer. Therefore, WebMax developed its innovative point-of-sale solution in 2017, called START, to not only meet the demands of borrowers, but to exceed their expectations and revolutionize the entire process. With START, WebMax provides a single location for the loan to exist for both the borrower and loan officer. There’s no shifting documents back and forth or waiting for verifications. START’s integrations to mission-critical third parties allows for the technology to do the work, streamlining workflows, reducing costs, and minimizing frustration.


PROGRESS in Lending has named Paradatec a top industry innovation. Other OCR solutions typically expect relevant data points to consistently appear in the same locations (or ‘zones’) on a document. If the data shifts due to changes in layout (again, think of bank statements), the zone-based approach will fail unless another layout template is created, making for a greater administrative burden with these solutions. A high volume, scalable OCR automation initiative requires the flexibility of Paradatec’s Advanced Mortgage OCR solution to process an unlimited number of document layouts without needing to develop specific templates for each layout variation. This capability is unique to Paradatec and a vital feature for creating an effective unstructured document classification and data capture solution. Paradatec’s Advanced Mortgage OCR solution is designed to make mortgage lending faster and more accurate. In 2017, Paradatec’s Mortgage OCR solution processed over 1,500,000,000 images (representing over 2,500,000 loans), helping lenders and servicers streamline their onboarding and compliance obligations.

Asurity Technologies

PROGRESS in Lending has named Asurity Technologies a top industry innovation. In 2017, MRGDocs was acquired by Asurity Technologies and introduced MRGDocs’ cloud-based platform which revolutionized the security of its dynamic document generation software featuring a secure system infrastructure to increase the protection of consumer data and deliver safer, faster, and more user-friendly systems while maintaining the content and support quality that has long been the hallmark of MRGDocs’ services and document packages. This solves for several mortgage industry challenges: the costs to secure big data, protecting the myriad of personal identification information collected, and managing compliance through a hyper secure platform. In 2017, MRGDocs built a comprehensive data security capability on a robust foundation that allows for the type of growth and expansion needed to serve even the largest of financial institutions, implementing a hyper-converged, virtual server platform with 24/7 SIEM-managed security monitoring.


PROGRESS in Lending has named STRATMOR Group a top industry innovation. MortgageSAT is an online customer satisfaction measurement program that allows consumers to provide direct feedback on their satisfaction with the mortgage process, and provides lenders actionable insights from the results, all available via an online portal. Put simply, it’s Business Intelligence based on consumer insights. Why did STRATMOR create MortgageSAT? For many years, mortgage lenders have struggled to capture actionable feedback from borrowers by means of post-closing email or closing-table-completed surveys. By means of its powerful borrower satisfaction management tool called MortgageSAT, developed in partnership with the CFI Group, STRATMOR has led the way to fundamental change the way lenders manage and apply borrower feedback. MortgageSAT is the first and only borrower satisfaction monitoring tool to score satisfaction at all levels of the organization as regards retail, consumer direct and broker production. As a consequence, many MortgageSAT clients tie their employee reviews and, in some cases, compensation both to these scores and a review of borrower comments. When everyone’s performance review includes a measure of their contribution to borrower satisfaction, a borrower-centric culture is fostered that is aligned with the emerging competitive paradigm of “optimizing the borrower experience.”


PROGRESS in Lending has named Maxwell at top industry innovation. No matter how digital the process, every mortgage is saddled with documents and data, over 500 pages, according to the Mortgage Bankers Association. As a result, an average of 20 days during the mortgage process is consumed by the search, preparation and review of those documents. Maxwell, the leading digital mortgage solution for small and midsize lenders, removes this friction with its platform. Sitting as the digital interface between the lender and their borrowers, Maxwell manages collaboration through the loan process, significantly reducing cycle times and driving delight. Originating teams on Maxwell are able to focus on what they do best, advising and coaching clients through the largest transaction of their lives, while Maxwell’s technology handles the rest. As one head of production attested, “Maxwell allows us to focus on what we love: working with real people. While loans get done faster and my team is happier.”


PROGRESS in Lending has named PromonTech a top industry innovation. The Borrower Wallet is the first offering from Promontory MortgagePath’s technology arm. From a lender’s perspective, the Borrower Wallet captures leads and fosters borrower/lender collaboration to drive enterprise efficiency and improve loan pull-through. In addition, its built-in collaboration tools deliver high-quality data and documents needed to feed and accelerate the downstream underwriting process. As a white-label offering, the Borrower Wallet makes the latest technology accessible and affordable to mid-size and smaller lenders, enabling them to compete with mega lenders. PromonTech’s culture of mutual respect between “techies” and mortgage industry experts made it possible to create a mass-market POS where both consumer and lender needs are equally important. The Borrower Wallet is not the first digital POS, but it’s the first to engage consumers while anticipating lender needs in such a balanced way. It combines creative design, industry analysis and data governance to create a unique user experience.


PROGRESS in Lending has named MCTlive! a top industry innovation. Over the past year, MCTlive! developed a major mortgage technology advancement with the addition of what the company branded its “Bulk Acquisition Manager” (BAM) solution, which is accessible via MCTlive! BAM is a Digital Loan Trading solution. BAM completely automates the process of packaging and transferring bulk loan bids, which benefits investors, lenders and MCT’s team of in-house mortgage loan traders. The result is a much quicker pricing process for bulk bid tapes, greater data security, better communication between counterparties, increased transparency for all parties, process consistency for investors within their existing platform, and centralization of data. BAM helps facilitate digitize loan trading on the secondary market. The effectiveness of the BAM technology has already gained 100% adoption by the ENTIRE investor community on the secondary market — across the board. And the level of transparency it offers between buyer and seller is hugely attractive and makes investors and lenders feel at ease.

Ellie Mae

PROGRESS in Lending has named the Ellie Mae Encompass NG Lending platform a top industry innovation. The Encompass NG Lending Platform allows lenders, service providers, and independent software vendors the ability to build custom applications in the cloud, integrate external systems and data, and extend Encompass in order to meet any and all industry challenges. Mortgage lenders and mortgage service providers can build, integrate, or customize solutions, and get them to their customers and market quickly. Lenders, partners, and third-party providers gain access to data and systems across the mortgage ecosystem. In the end, all participants can easily view and share loan date, sales pipeline, loan events, documents, and order services. A shared system of record allows all parties in the loan process to see the same up-to-to-date information in the same format. Everyone in the ecosystem can easily share, interact, and collaborate without having to create and support new channels.



Tried & True Innovation

As we all know, mortgage lenders are looking for an edge. How do they get that edge? They can start by replacing a paper-driven mortgage process with an automated process. This is where industry specialists like Paradatec can help. For over two decades, Paradatec has focused its skills towards delivering the most efficient, accurate, and flexible freeform document classification and data extraction solution available anywhere. Specifically, Paradatec’s advanced OCR solutions offer significant efficiencies for classifying large quantities of differing document types and extracting key data elements from those documents. In the mortgage market, these out-of-the-box capabilities allow for the quick and accurate identification of nearly 500 unique documents in the typical mortgage file, along with capturing over 6,000 data elements from those documents. Our editor talked to (left to right) Mark Tinkham, the company’s Director of Business Alliances; Paul Fischer, the company’s Director of Professional Services; and Neil Fraser, the company’s Director of US Operations; about how lenders can use technology to improve the mortgage process. Here’s what they said:

Q: So, what does Paradatec specifically do that would be compelling to a mortgage servicing, or lending operation?

MARK TINKHAM: Paradatec streamlines and monitors processes which otherwise require significant human labor. We minimize the need for managing large costly staffs of trained loan file indexers and data key entry operators. We do this while at the same time providing statistical feedback and measurement of accuracy and automation. We provide these efficiencies so that our clients are able to better focus on their customers, manage workload peaks and valleys more easily, and measure results over time.

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A good basic example is our ability to automatically identify all the documents in a 500 to 1,000 page loan package, and capture every one of the hundreds of fields on every version of every TRID document (Loan Estimate and Closing Disclosure), every one of the dozens of fields on a Loan Application, Appraisal, Transmittal Summary, Note, Deed of Trust, 4506-T, Income Tax statement and whatever else a client may require.

Q: How does OCR (Optical Character Recognition) technology provide value in today’s Mortgage Industry?

PAUL FISCHER: There are vast differences between some of the lower cost OCR technologies, and the advanced OCR offered by Paradatec. The advantages to using our technology are a dramatically faster, more accurate and less costly process for indexing and capturing data from mortgage loan documents.

The short answer to your question is: we provide our clients with an ability to do in seconds what many operations, using 100% human labor, take hours to do. And, at the same time, we provide results which are more accurate.

Our unique approach to OCR allows us to extend these broad benefits to originators’ and correspondent lenders’ indexing and data ingestion validation, and servicers’ loan onboarding processes.

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Our capabilities, out of the box, today include rules to identify approximately 500 mortgage loan document types and extract more than 6,000 fields from those documents.

In addition, we have helped our clients with automating their compliance processes with HMDA loan audits, UCD creation and TRID capture solutions.

Q: Has the industry fully embraced your automation technology?

NEIL FRASER: We think lenders do understand the need for automation, but many may not be aware of the significant and unique competitive advantages our clients continue to realize.

Lately we have been spending more time sharing our many success stories and getting the word out that we can provide powerful efficiencies related to loan automation.   These advantages range from compressing the time it takes to process borrower-provided documents to expediting the loan onboarding process and making compliance audits significantly more automated.

We offer an ability to dramatically reduce the manual efforts related to indexing loan documents, and capturing key data from those document images. Our sub-second per image processing speed is unique and it allows us to take an approach which others are unable to match due to their OCR performance. This speed and ability to scale our processes to tens of millions of images per day on a small hardware footprint are waking up the industry to the possibilities of how their operations will benefit.

So, we are seeing more and more lenders embracing our technology. And, because we continue to add enhancements and find new ways to provide value with our technology we believe our current and future clients will continue to find new and exciting ways to further embrace our solutions.

Q: How is Paradatec’s OCR technology different than others?

MARK TINKHAM: Our extreme focus on OCR technology began more than twenty-five years ago, and since 2007 we have been applying our unique, sub-second per page, small hardware footprint OCR technology to the mortgage industry. With every implementation, we have continued to build more and more out-of-the-box capabilities specific to processing mortgage loan documents. Over the years we have seen various fads and splashy marketing campaigns touting various OCR technologies and approaches, which in reality were not effective.

Recently we’ve seen an increase in the hype with alternative automation strategies. One approach, which isn’t new, and we have seen in years past, is something called visual classification, in which the image ‘fingerprint’ of a page is used for identification rather than the text itself. This approach is fast and used in an attempt at matching our sub-second per page processing speed.

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For documents that are graphically focused with minimal text, this may work fine, but mortgage files are loaded with text, and in many cases that text will be key to correctly identifying the document type. For example, many Deed and Rider signature pages can look similar, in that the content many times pushes the signature block to its own page. Our clients want the delineation between these docs, and even between the various Riders, but at a ‘fingerprint’ level these pages can look quite similar, leading to many indexing errors. It’s only when the footer text is discovered and read as “PUD Rider,” “MERS Rider,” or “Deed of Trust” that the correct automated decision can be made, which our solution completes with sub-second speed.

Q: How do you ensure quality control and data accuracy?

PAUL FISCHER: We implement database validation of captured data, and reasonability rules for indexing and data capture. In addition, we provide a process for statistically random reviews and measurements of loan indexing and captured data along with an ability to track user efficiency over time. With the Paradatec Statistics database, our clients are able to generate an unlimited number of useful reports which track processing time, by loan, by user, by time period, even down to the document type and extracted data field level.

In addition, we provide an ability to create a quality review and learning process from production output with our analytical tools. This process is performed as part of the testing and implementation stages, and provides deep insights into the accuracy and automation levels which have been achieved.

As part of an ongoing quality measurement and learning adjustment stage, our clients can be confident that their processes are continuing to perform at the highest levels of quality.

Q: Your Company has released an Application Programming Interface (API). In layman’s terms, what does this do?

PARADATEC: We provide a Web Services API which allows end users to submit loan documents and data for validation to our workflow processes from virtually anywhere.

A use case example would be our OnDemandOCR process, which utilizes our API to allow lenders to submit final Closing Disclosures remotely and receive a MISMO formatted GSE compliant Uniform Closing Dataset (UCD) back as output for review and ultimately submission to the GSEs when loans are presented.

Another use case for our API will allow borrowers to submit documents as part of a loan origination. Our OnDemandOCR process will then identify the document or documents submitted, and automatically extract the key data fields from them.

Q: What are some other manual processes that you have automated within your clients’ operations?

NEIL FRASER: Since our focus on the mortgage industry began, we have continued to find more and more new, and many times dramatic ways to enhance our clients’ processes.

A little over a year ago, we were asked to re-index approximately two million loans due to some compliance pressure our client was getting to make sure their loan portfolio accurately accounted for the necessary source documents. We were able to assist by processing over 1.2 billion document images in a matter of weeks. In other cases we have been asked to help meet new compliance obligations by significantly streamlining what would otherwise have been extremely costly, labor-intensive efforts.

Our new HMDA Audit capability enables our clients to quickly validate the data on their Loan Application Register (LAR) against the data found on the associated loan source documents. Each loan is processed at less than one second per page and each of the final source documents’ data is compared to the values on the LAR. This process allows our clients to ensure compliance with the Federal Reserve Board’s Regulation C before submission to the Federal Financial Institutions Examination Council (FFIEC).

Our UCD Audit capability enables our clients and the GSEs to automatically compare the MISMO 3.3 data found in a Uniform Closing Dataset against the corresponding values found on the final Closing Disclosure which is embedded in that UCD. This process is performed at an average of one second per page and each of approximately 300 fields extracted are then compared. Differences found between the MISMO data and the extracted data are reported in a MISMO compliant “differences” file. Along with this, we also produce a corrected UCD based on the embedded Closing Disclosure.

Our CCAR FRY_14M offering helps our largest clients comply with the latest CFO attestation requirements related to the Dodd-Frank Stress Test rules for large financial institutions. This process uses our high speed OCR capability and pre-built rules to classify documents, find the final version of key document types, and validate source document data against attestation data. This process can be performed in seconds per loan, and allows our clients to find and correct much of the inaccuracies typically found. In fact, because the original attestation data is typically key entered with human labor, and final document versions are often confused with non-final versions, prior attestation data is often incorrect. Without automation, this compliance risk mitigation step would be cost prohibitive.

Q: Paradatec has more than a decade of experience within the mortgage industry. What new initiatives and innovations have you recently brought to market or have coming up in the near future?

MARK TINKHAM: Some examples of new initiatives, new capabilities, and product features, some of which were mentioned earlier, include:

The Paradatec WriteUCD module for automated creation of GSE compliant UCDs from final Closing Disclosures.

Web Services API to enable our clients to seamlessly integrate our technology using our OnDemandOCR feature.

An ability to capture every field on every version of both the Closing Disclosure, and the Loan Estimate in an average of one second per page.

Our Paradatec WritePDF module for creating fully indexed loans with data fields highlighted in a PDF which includes a table of contents which virtually maps a loan’s documents and key source data.

An ability to automatically identify and capture all the fields on the new HMDA compliant URLA and the new HMDA addendum to the old URLA.

Our new HMDA audit process which can greatly streamline this process for our clients.

Our UCD Audit capability has attracted some significant interest from the GSEs and some of our larger clients.

We’re developing a new handprint discovery feature that will provide large leaps in automation for our post-close clients, which need to validate the required initials and signatures on key loan documents.

Q: How do you see the mortgage industry and the mortgage process of the future evolving?

MARK TINKHAM: Like many other industries, the mortgage industry is experiencing an evolution through the aid of technology. Staying competitive and reducing per-loan processing costs require the use of technology like ours. Industry leaders such as Amazon and Orbitz have made the self-service model, albeit in other market segments, much less daunting, and the speed at which transactions can be completed has decreased significantly through this evolution. While the magnitude of the buying decision for a home is obviously much greater than that of buying an airplane ticket or a pair of shoes, the consumer has become comfortable with online transactions to the point that a paper-bound process is viewed as slow and stodgy.


Mark Tinkham is Director of Business Alliances at Paradatec, Inc. Over the past twenty-five plus years, Mark has worked for technology companies that deliver innovative solutions to the financial services industry. For the past ten years, his primary focus has been bringing efficiencies to the mortgage market through industry leading Optical Character Recognition (OCR).


Mark Tinkham thinks:

1.) The digital mortgage won’t eliminate the need for manual data entry.

2.) Our UCD Audit process will be found to be an invaluable tool for those lenders selling loans to the GSEs.

3.) The 20 largest lenders and servicers will all embrace advanced OCR by 2020 out of necessity.


Paul Fischer is Director of Professional Services at Paradatec, Inc.  For nearly 15 years he has focused on the design and installation of document capture, content management, and workflow automation systems for clients in a variety of industries.  Since joining Paradatec in early 2013, his primary focus has been on helping mortgage clients improve their operational efficiencies with Paradatec’s advanced mortgage OCR solution.


Paul Fischer thinks:

1.) Cycle times and cost pressures will continue to drive automation initiatives in the mortgage origination and servicing space.

2.) Document ingestion for mortgage servicing rights (MSR) transfers will become an entirely automated process.

3.) Robotic process automation (RPA) will reduce manual labor by 20% and much more in many cases.


Neil Fraser is Director of US Operations at Paradatec, a mortgage OCR technology organization that automates the data entry operations of large lenders through intelligent document analysis. Neil was Paradatec’s first US employee and has grown the organization every year since the company incorporated here in 2002.


Neil Fraser thinks:

1.) Redaction of personally identifiable information (PII) will become ubiquitous for any mortgage documents leaving a lender.

2.) Audits involving regulation such as TRID, RESPA, HMDA etc will become automated.

3.) As more investors move back into the secondary markets, the need for an audit trail from documents to elements in a loan servicing system database will become a requirement.

Coping With Doc Management Complexities

The lending industry faces the challenge of managing very large volumes of unstructured documents that contain immense amounts of critical data. The process of classifying and keying data from these documents is labor intensive, time consuming and costly due to the sheer volume and complexity of the documents. In an industry where standardizing forms is not possible due to their varying sources and wide variety, an acceptable solution must be able to cope with this complexity.

Founded in 1993, Franklin American Mortgage Company (FAMC), a privately held mortgage-banking firm located in Franklin, Tennessee, is a full-service professional mortgage banker licensed to provide residential mortgages across the nation. FAMC, which offers a host of diverse, flexible mortgage packages for customers with a variety of backgrounds and needs, is committed to helping families and individuals achieve the dream of home ownership through its three divisions: retail, wholesale and correspondent.

FAMC offers borrowers, brokers and lenders the strength and security of a forward-thinking national mortgage company, dedicated to remaining an industry trendsetter. FAMC truly values its relationship with each customer and mortgage professional they work with, maintaining a company tradition of responsiveness and personalized service characteristic of a much smaller organization. This philosophy has enabled FAMC to become one of the fastest growing mortgage bankers in the nation.

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The Challenge

The Mortgage lending industry presents a number of unique challenges for manually classifying and managing very large volumes of disparate documents, which are ubiquitous within this industry.

>>It is common for a single mortgage loan to be comprised of over 250-500 pages of various size documents.

>>A mortgage loan may include over 275 different possible document types.

>>Manually sorting each set of loan documents can be a very labor intensive and error fraught effort.

>>When scanning loan documents, significant labor is required to simply establish the first and last pages of the multiple page documents. This is most often done using the costly process of inserting “document separator” sheets prior to scanning.

>>To compete in this extremely competitive business, organizations need to look at cutting costs and streamlining their processes.

Manually preparing a batch for scanning by inserting document separator sheets and manually classifying loan documents is a labor-intensive process. Not only is it critical that this process be done accurately, but also that it be done efficiently in order to allow downstream underwriting and servicing decisions to be performed in a timely way.

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Project Description

Franklin American Mortgage Company (FAMC) had been looking for an OCR technology vendor to streamline their ADR process and had spent a significant amount of time performing a due diligence process, which compared vendors of these technologies.

“We had attempted to use OCR in the past for Automated Document Recognition (ADR). Due to our prior experience and a variety of technical issues we were very skeptical about OCR.”

Because of the extremely large number of, and variations of forms FAMC encounters, they required the flexibility offered by a non-template-based solution. In addition, the ideal solution needed to offer pre-built mortgage logic that would “understand” the vast majority of the document types and variations FAMC was required to recognize. This logic would allow FAMC to rapidly develop a customized ADR solution to their specific needs using the ideal solutions copyrighted mortgage rules as its foundation.

Today, FAMC scans millions of pages of mortgage documents per month. They no longer require their employees to insert document separator sheets to prepare a loan for the scanning process.   Once scanned, the loans are processed using the industry leading OCR solution for automated document recognition.

Documents’ boundaries (first and last pages) are defined and their types are automatically identified. These processes are now done faster and with a fraction of the labor formerly required. To ensure extreme accuracy, sophisticated mortgage-lending business rules have been implemented as part of the solutions exception process.

Additional capabilities leveraged successfully at FAMC:

>>Verification provides list of very likely document types to further increase speed of verifying exceptions.

>>Ability to customize how documents are handled based on the division of business the documents come from.

>>Ability to quickly add new document types using the Paradatec exclusive automated learning objects.

>>Database lookups and business rule logic checks to ensure the highest degree of accuracy.

>>No scripting interface, easily configurable rules to manage FAMCs highly sophisticated ADR processing application.


The project was completed and is currently in production. The system is able to achieve 80% document recognition while keeping error rates low. This has allowed FAMC to position itself for an anticipated future increase in incoming document volume and provides them with a powerful competitive advantage. Today FAMC is processing Millions of images per month and doing all this more accurately and with less production time than was formerly required.

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“We asked a number of vendors including the Paradatec team to help us perform an extensive due diligence process which included a proof of concept test with our own documents. Paradatec was the clear winner based on our comprehensive vetting process”.

Paradatec’s PROSAR-AIDA is an advanced and unique OCR recognition technology. It is unique in that it utilizes neural networks technology and Artificial Intelligence (AI). PROSAR-AIDA is able to read structured, semi-structured, and unstructured documents. It makes ‘decisions’ about document characteristics in much the same way as a human being does, only many times faster and without human intervention.

PROSAR-AIDA takes a very different approach than other technologies. Because the recognition engine (a Paradatec exclusive) incorporated in PROSAR-AIDA is faster than any full page OCR product on the market, it is able to process each image, in less than two seconds on average. It does this without making any assumptions about content location on the page or attempts at matching zonal OCR templates. PROSAR-AIDA is capable of processing thousands of documents per hour with a single processor core, and provides even further almost unlimited scalability by offering seamless utilization of the latest in multi-core processor technologies, and multi-server environments.

Because of Paradatec’s unique approach, and their ability to leverage a vast quantity of intellectual property, which they have built over the years specifically for mortgage loans, implementations can be completed in a fraction of the time normally required by others.

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Loan Document Automation

The mortgage lending industry presents a number of unique challenges for classifying and extracting data from key documents, due in part to the large volumes of disparate documents in most loan files.

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New documents and the regulations related to them put a new emphasis on the need for quick and very accurate data. Lenders in particular face significant penalties for inaccurate data and missed delivery deadlines. Sorting and capturing critical data from thousands of diverse documents has historically been labor intensive, slow, and expensive. To stay competitive, and meet these new and constantly changing challenges, automation through technology is no longer optional.

The key is finding a provider that specializes in automated document classification and data capture specifically for mortgage lending and the financial services industries, which scales to process millions of pages per day.

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Leading edge OCR solutions offer significant efficiencies for classifying large quantities of differing document types and extracting key data elements from those documents.  In the mortgage market, these capabilities allow for quick and accurate identification of over 500 unique documents in the typical mortgage file, along with the ability to capture nearly any data element from those documents that an organization requires.

Here are some examples of applying this advanced technology to specific mortgage documents:

Application Processing

Extract relevant content from borrower-provided pay stubs, W-2s, bank statements, and tax documents to expedite underwriting and reduce origination costs.

Post-Close Processing

Identification of each document in the loan file, bringing structure to what was a 300+ page blob of content.

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Verification that relevant documents have been signed

Compare key data elements from loan file with your systems of record to verify changes haven’t been made without your knowledge.

UCD File Generation

Create the Uniform Closing Dataset (“UCD”) file required (as of Sept 25, 2017) when selling loans to Fannie Mae and Freddie Mac

Reporting And Audit Automation

Extract key loan file data elements to support the following reporting/audit activities:

HMDA reporting – our system is ready to capture the additional demographic data on the new Uniform Residential Loan Application (effective Jan 1, 2018)

RESPA audit

TRID audit

Lenders can longer afford to manually classify and manage large volumes of disparate documents. Manually preparing a batch for scanning by inserting document separator sheets and manually classifying loan documents is a labor-intensive, inefficient and error prone process. Not only is it critical that this process be done accurately, but also that it be done efficiently in order to allow downstream underwriting and servicing decisions to be performed in a timely way.

At the end of the day it is about finding a provider that focuses its skills towards delivering the most efficient, accurate, and flexible freeform document classification and data extraction solution available. The time is now for lenders to reduces manual labor costs and increases accuracy levels associated with classifying and capturing data from loan documents.

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