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.

Fears Abound

The smart lender sees what’s going on. A lot is changing. One big concern is the interest rate environment.

So, are fears of rising interest rates overblown? If not, why? How can lenders bring in more buyers?

“No. Fears are not overblown because margins have declined,” answered Les Parker of LoanLogics. “Production is tied to seasonality, but the gain per loan has decreased, which is significant. Cash-out refis are not picking up like most anticipated. The move to higher rates speaks to the lack of scalability of independent mortgage bankers.

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“As a result, lenders are trying to broaden their product base. The challenge is that as you expand your products you also have to expand quality control. Lenders are also increasing the commissions to loan officers, which decreases margins and further hides their ability to scale.”

Les Parker is a consultant to LoanLogics. He is a contributor to the company’s strategic planning team and helps to facilitate communications with industry leaders on its behalf.

Parker has executive mortgage banking experience in capital markets, servicing, operations, production and financial management. Parker has served as director of the largest private issuer of CMOs. His educational background covers music, religious studies, mortgage banking, mathematics, and business administration.

Parker holds a BBA in Finance, other degrees, and has held numerous securities licenses. Parker is a Master Certified Mortgage Banker, a designation conferred by the Mortgage Bankers Association.

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“Overall volume hasn’t gone down,” noted Tom Millon, founder of Capital Markets Cooperative. “We are seeing volume at assumed levels. It’s all about purchases and a lack of inventory vs. a lack of borrowers. Broadening the product menu would be a good way to attract new borrowers.

Specifically, Tom Millon founded Capital Markets Cooperative (“CMC”) in 2003 and is considered one of the nation’s top executives in the mortgage capital markets. Tom is a recognized author, frequent speaker, and expert in mortgage finance. He serves as President, Chief Executive Officer, and Chairman of CMC, and is the Chief Executive Officer and Chairman of CMC’s lending subsidiary, CMC Funding, Inc.

Tom is a member of the Mortgage Bankers Association where he serves on the MBA’s committee for GSE reform. Tom is also on the advisory board of the Common Securitization Platform—a joint venture between Fannie Mae and Freddie Mac, dedicated to standardizing the agency mortgage-backed security.

Tom holds the Chartered Financial Analyst and Certified Mortgage Banker designations. He is FINRA Series 3 licensed and is a member of the National Futures Association, the Association for Investment Management and Research, and the Security Analysts Society of San Francisco.

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“To counteract current trends lenders have to act boldly. Acting boldly is hard to do, but it is necessary,” said Millon. “I think lenders view certain loan products as being too risky to originate from a regulatory standpoint, so they resist.

“We offer technology solutions and investor solutions across the whole lifecycle of the loan. Lenders want to keep their costs going in the right direction. Lenders want to be disruptive and try to get a huge advantage if possible. So, they have to look at technology,” concluded Millon.

“Going forward, the refi market will be cut out, but you have a historic number of new borrowers coming in,” added Jim Pippin, director of client solutions at National Mortgage Insurance Corp. (national MI). “Reaching into the multicultural market is important. A lot of minority homebuyers still think they need 20% down and nobody is marketing to them. Also, Millennials have similar misconceptions. You have to reach them in a new way because they prefer to be reached via social media.”

Jim Pippin is director of client solutions at National Mortgage Insurance Corp. (National MI), a subsidiary of NMI Holdings, Inc. (NASDAQ: NMIH). National MI is a private mortgage insurer based in Emeryville, CA. Pippin is involved in all facets of product development and launch, including design, pricing, operations and sales training. Prior to National MI, Pippin held senior positions at Genworth, Bank of America, Capital One and General Electric, where he earned a Six Sigma Black Belt. He holds a B.S. in Industrial Engineering from North Carolina State and an MBA in Business Administration from Wake Forest University.

“We see a lot of utilization of FHA when it doesn’t really suite that borrower. It is getting overused,” continued Pippin. “Also, there is a perception that MI is not a favorable part of the industry, but MI helps to drive the market

“A lot of what we do is help lenders figure out what to do when the phone stops ringing. We help lenders go out and get those new borrowers. Borrowers need to be more educated and approached.”

“I believe that lenders miss the biggest threat to their business model,” added Parker. “The big threat is competition from a new entrant that does things better vs. the guy down the street. Lenders have a tendency to think the sales model that they are competing against is a company with the same sales model, but that’s not true because there are a lot of new entrants that are trying to change the traditional model.

“The greatest issue is fear to take bold action and raise capital to take that action. They can ask questions and get advice. From there they can go to the technology vendor with a plan. Generally, lenders are optimistic and they have a plan, but they have to build that consensus across their company. Lenders have to address threats head on and engage with consultants to get good advice,” concluded Parker.

About The Author

5 Ways Giving Employees A Stronger Voice Can Make Your Company Sing

Many employees feel management is deaf when it comes to hearing their concerns and considering their ideas. Don’t they? Apparently, yes. You bet that they do. That has to change in order for your company to be really successful.

“Employee voice” in the workforce has become a catchphrase in human resource departments as companies see the benefits of opening their ears to their employees. The Society for Industrial and Organizational Psychology last year listed “capturing the employee voice” as the No. 7 workplace trend.

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Research ties in employee voice, among several factors, with employee engagement. A Gallup poll revealed that more than half of U.S. employees were “not engaged.” I think giving employees a voice leads to more engagement on multiple levels – and more successful companies.

When we provide employees with access to the corporate microphone, the music can be instantaneous and breathtaking. Companies are constantly striving to please their customers, but the same vital attention needs to be given to their strongest asset, the employees.

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When employees are given a voice, it makes all the difference, building trust, bringing a higher level of performance, and leading to success for all.

I suggest five ways that giving employees a voice benefits a business:

Discovers hidden talent. People who were buried deep in the organizational chart bring solutions with their fresh perspective and broadened roles. Once viewed as disengaged, they are seen in a new light, now fully utilized and helping the company to prosper. By inviting more ideas, you’ve opened up a new world for your organization.

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Increases camaraderie, enhances culture. The mood shoots up when everyone suddenly feels more valued by being heard. You will be pleasantly surprised by the smiling faces and camaraderie that return to your employee base. Employees love working in an environment where everyone is really listened to and their ideas matter.

Energizes, drives productivity. A happier, more appreciated work culture leads to a more energized workforce. When employees start feeling heard – seeing ideas implemented, and knowing they have real input – it encourages buy-in and even more effort, so productivity goes up.

Diagnoses, clarifies. Getting to the source of problems means getting to the truth, and without repercussions in telling it. This clears obstacles. And by bouncing ideas off others, hearing their concerns and perspectives, you stay true to company goals and improve the company’s way of getting there.

Identifies future leaders. Empowering everyone by giving them a voice inspires confidence, allowing leaders to emerge. Some may not initially see themselves that way, but they will be self-evident by the clarity of their reasoning and the courage of their convictions. Good management unlocks potential, empowers it, and here is another example of that.

The results of this dramatically improved communication between employer and employee are immediate and lasting. The relationship is enhanced in multiple, measurable ways.

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Let’s Do This Right

Now is the time to think about holistic marketing. Why? We all know that the current mortgage market has its challenges. But that’s no reason to give up. Now is the time to hone your marketing so you are the company of choice.

In the article entitled “The Best of B2B Marketing Content: 10 Examples” written by Meghan Keaney Anderson, she says that many B2B marketers have seen B2C content at least once and asked, “Why do they get to have all the fun?” But the moments like the one we described above are the ones that remind us: B2B companies are just as passionate about their products as B2C companies are. And for every B2B product, there are even more B2B users out there looking for information, inspiration, and knowledge to provide them with solutions.

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So, what’s the point? No marketing, including content, is uninteresting if you look at it certain ways. Done right, B2B content marketing can certainly match — and sometimes, maybe even rival — the creativity and appeal of the best B2C ones. Here are some tips:

Remember Your Buyer’s Goals

When you’re dying to create truly unique, cutting-edge content, it’s easy to stray from your organization’s mission and focus. So, while it’s great to think outside of the box, use clever subject lines, or even write every email with an overarching humorous tone, keep it relevant and include the information that the people reading it signed up to receive in the first place. Then, keep it human.

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Educate Your Buyers

Think about the problems that your product or service already aims to solve for customers. Then, turn that into relevant content that’s going to both save time for and inform your audience, and make it easy for them to access it.

Grow With Your Buyers

When you begin to brainstorm and map out ideas for content, ask yourself, “Do I really understand my audience?” If you have any doubts as to how the idea will benefit or be useful to your audience, the answer might be “no” — and that’s okay. Like everything else, audiences (and people) evolve, so it’s okay to go back to the drawing board in instances like these for a refresh.

Diversify Your Channels

The Internet is only going to become more crowded. And as the human attention span dwindles, that makes it even more important to create content that engages and maintains your audience’s attention.

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So while we don’t recommend abandoning blogs completely, after all, written content is still vital to SEO, we do emphasize the importance of diversifying content formats. Marketers who incorporate video into their content strategies, for example, have seen 49% faster revenue growth than those who don’t. And remember that tip to “keep it human” we mentioned earlier? That’s a great thing about live video in particular, it can help portray brands (and their people) as candid and genuine.

Work With Thought Leaders

If you’ve ever wondered how to leverage the wealth of knowledge outside of your organization, and inside your professional network, here’s a great example.

Don’t be afraid to reach out to the entrepreneurs and leaders you’ve met, or simply just admire, to figure out how they can work with you to create content with teachable experiences that your audience will value. Sharing useful, relatable first-hand accounts conveys empathy, which helps to invoke trust among readers.

Publish Off-Domain Content

Take advantage of the availability of off-site content platforms. As my colleague, Sam Mallikarjunan, writes in “Why Medium Works,” it can take up to six months of consistent publishing on your company’s blog before it gains significant traction. (And we’re not discouraging that, stick with it, and find ways to supplement those efforts.) But off-site content diversifies your audience by engaging readers who might not have otherwise found your website.

Medium, for example, connects your content with the people most likely to read it. Plus, you’re creating a publication on a platform that comes with a built-in audience of at least 6.3 million users.

Incorporate Visual Content

Please, please, please don’t neglect to incorporate visuals into your content strategy. Of course, having a presence on visually-focused channels like Instagram and YouTube is vital, but when it comes to your written content, don’t afraid to use visuals there, as well. After all, articles with an image once every 75-100words got double the number of social shares than articles with fewer images.

But if you can also create content that aligns with the core of your product or service, that’s also great. For example, Wistia creates visual content technology, so it makes sense that it would have unique visual content. Identify what your business does particularly well, and then make the most use of the channel that best aligns with your strengths.

Tell Your Brand Story

Dig beneath the surface of the solutions your company provides. You offer solutions, but what is your process? What have you learned that makes you do what you do so well, and how did you get there?

Sure, topics like engineering might be traditionally “unsexy.” But when leveraged and communicated in a storytelling manner, they can make for remarkable content.

Challenge Your Buyers

It’s easy to feel limited by your medium as you create content, especially for a business audience who you’ve all agreed is comfortable with that medium.

But in order for content to convert readers and incite growth, it needs to occasionally disrupt its audience’s point of view. A company doesn’t work for its content; content works for its company. If you need to say something that a blog alone can’t, the business demands that you make it work, whether that means starting a YouTube channel or seeing how you can integrate an AR tool into your next ebook.

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Financial Illiteracy Is Harming Americans

America is consumed with higher education – going to college and earning a degree as the necessary means to a well-paying job.

Yet with parents emphasizing the importance of academic excellence, and their children graduating and going on to successful employment, why do many still remain uneducated in fundamental financial matters?

Numerous statistics show financial illiteracy is a major problem in the U.S., reflected in enormous personal debt, woefully small savings, and irresponsible spending. Despite being home to many millionaires and billionaires, the U.S. ranks only 14th in the world in financial literacy, according to Financial Literacy Around the World, a Standard and Poor’s Rating Services Survey.

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A lack of knowledge or interest in financial matters comes from the family culture early on, and often as adults people have to teach themselves. They’re not teaching financial literacy in high school, certainly not even the basics, like how compound interest works.

People need to self-educate and research. All the information is out there. Financial illiteracy is a widespread problem and its consequences reach far, from having no emergency funds to having little set aside for retirement.

Joyce comments on three areas where the costly effects of financial illiteracy are significantly felt:

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Low Savings. A 2017 survey of more than 8,000 people by GOBankingRates found that 57 percent had less than $1,000 in their savings account.

There’s an overall lack of education there as well from our schools. But at home if you don’t set examples for your children, I don’t think it will ever change. At the end of the day, you’ve got to put a little aside and say to yourself, ‘I’m not going to touch it.’

Credit card debt. In December, NerdWallet revealed in its Household Credit Card Debt Study that the average American household owes $15,654 in credit card debt. Forty-one percent in the study admitted to spending more than they should, which leads to paying more interest and lingering high debt.

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It’s a lack of discipline and not knowing the effect of interest rates. Most people are well-educated enough to understand what living outside their means actually means. But many adults act like a child making a decision and not really thinking about the consequences until they actually happen. This is especially true with the younger generation. The way the world is progressing with technology makes it easier to buy, and I think people easily get trapped in that.

College debt. Five-figure college loan debts are common and continue to be a major drag on the economy. Joyce says parents of normal to low-income means might want to re-evaluate saddling their child and themselves with such a burden. But he also points the finger at colleges and employers.

The colleges are to blame as well, because they make it seem as though in order to get a good job, everybody must go to college. There’s nothing wrong with trade school. The cost of college is ridiculous. And I think employers can do a better job of having a benefits package that would absorb a lot of that college debt cost for a long-term valuable employee.

People lack financial discipline. They need to stop and think about their needs versus their wants, about their short-term and long-term goals.

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Data: Property Taxes Are On The Rise

ATTOM Data Solutions released its 2017 property tax analysis for more than 86 million U.S. single family homes, which shows that property taxes levied on single family homes in 2017 totaled $293.4 billion, up 6 percent from $277.7 billion in 2016 and an average of $3,399 per home — an effective tax rate of 1.17 percent.

The average property taxes of $3,399 for a single family home in 2017 was up 3 percent from the average property tax of $3,296 in 2016, and the effective property tax rate of 1.17 percent in 2017 was up from the effective property tax rate of 1.15 percent in 2016.

The report analyzed property tax data collected from county tax assessor offices nationwide at the state, metro and county levels along with estimated market values of single family homes calculated using an automated valuation model (AVM). The effective tax rate was the average annual property tax expressed as a percentage of the average estimated market value of homes in each geographic area.

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States with the highest effective property tax rates were New Jersey (2.28 percent), Illinois (2.22 percent), Vermont (2.19 percent), Texas (2.15 percent), and New Hampshire (2.06 percent).

Other states in the top 10 for highest effective property tax rates were Pennsylvania (2.02 percent), Connecticut (1.99 percent), New York (1.92 percent), Ohio (1.72 percent), and Wisconsin (1.67 percent).

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Among 217 metropolitan statistical areas analyzed in the report with a population of at least 200,000, those with the highest effective property tax rates were Scranton, Pennsylvania (3.93 percent); Binghamton, New York (3.14 percent); Rockford, Illinois (3.03 percent); Rochester, New York (2.93 percent); and El Paso Texas (2.63 percent).

Out of the 217 metropolitan statistical areas analyzed in the report, 125 (58 percent) posted an increase in average property taxes above the national average of 3 percent, including Los Angeles (7 percent increase), Dallas (11 percent increase), Houston (10 percent increase), Philadelphia (4 percent increase), and Miami (5 percent increase).

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Other major markets posting an increase in average property taxes that was above the national average were Atlanta (up 4 percent), Boston (up 5 percent), San Francisco (up 6 percent), Riverside-San Bernardino (up 5 percent), and Seattle (up 6 percent).

States with the lowest effective property tax rates were Hawaii (0.34 percent); Alabama (0.49 percent); Colorado (0.51 percent); Tennessee (0.56 percent); and West Virginia (0.57 percent). Other states in the top 10 for lowest effective property tax rates were Utah (0.58 percent), Delaware (0.61 percent), South Carolina (0.66 percent), Arkansas (0.68 percent), and Arizona (0.68 percent).

Among the 217 metro areas analyzed for the report, those with the lowest effective property tax rates were Honolulu (0.33 percent); Montgomery, Alabama (0.36 percent); Tuscaloosa, Alabama (0.41 percent); Colorado Springs, Colorado (0.42 percent); and Greeley, Colorado (0.45 percent).

The Risks And Rewards Of Artificial Intelligence For Lenders

In looking at this, the recent debut of self-driving cars could transform a stressful commute into an opportunity to tackle emails and reading lists while making suburban long-distance travel great again. Americans are poised to gain more than 100 hours per year in free time by relinquishing the wheel to smart cars. The downside, though, lies in inevitable vulnerabilities like security threats, job loss, and environmental impact. Is the reward of AI worth the risk?

Artificial Intelligence is broadly defined as a computer’s ability to perform tasks normally requiring human intelligence. Ever since Alan Turing developed a test to determine a machine’s ability to exhibit intelligent behavior in 1950, roboticists and scientists have sought to pass it. In 2014, a computer program called “Eugene Goostman” succeeded by convincing 33% of the human judges that it, too, was human. Since then, companies like SAP, General Electric, and MasterCard have utilized machine learning and artificial intelligence (MLAI) to identify trends and insights, make predictions, and influence business decisions.

Artificial intelligence offers new opportunities to revolutionize operations in the financial services industry. Machine learning can process terabytes of data in seconds – volume which a horde of humans with older machines or methods could not process in a lifetime. The sheer power of modern computing in assessing an increasing number of variables with speed and accuracy gives a financial institution the ability to have rapid and strategic insights about customer behavior, reporting errors, and risk patterns. In the area of loan decisioning, this should lead to faster loan origination, fewer compliance problems with regulatory fines, and more inclusive lending overall.

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We wanted to know: What are the risks and rewards of AI in lending, and is it an inevitable next step for compliance management?

Bob Birmingham, CCO of ZestFinance, and Dr. Anurag Agarwal, President of RiskExec at Asurity Technologies, explore.

Which Discrimination Would You Prefer: Human Or Machine?

Anurag Agarwal: With machine learning, the decision-making is supposedly agnostic to overt biases. Humans, by definition, are free thinking but with biases that interfere with decision-making, especially in lending scenarios.

Bob Birmingham: AI is not a product but a solution, another approach to problem solving using advanced mathematics, analytics, and data. It’s not a magic fix but can remove some of the human discretion that leads to discrimination.

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AA: The problem is that computers could reinforce societal disadvantages by relying too heavily on data patterns. When a machine imports data, it creates an algorithm but cannot explain its methodology. It may introduce variations in the mix without understanding the broader implications.

Say you are trying to determine the risk of repayment for a borrower. The machine identifies physical appearance as a decision point. Based on data patterns, it detects that blue eyed individuals are more prone to timely repayment of loans. Noticing a correlation, it elevates that decision point to a higher influence in future lending. By taking an apparently agnostic data element and making a correlation it has in essence created discrimination because it doesn’t understand that blue eyes are mostly representative of Caucasians and the societal implications of making that borrower preference as a result.

BB: We’ve been here before as an industry. When regression modeling first came out it was confusing, flawed, and its accuracy questioned. At the end of the day, it was actually a more accurate process than purely judgmental underwriting because it followed a clear set of instructions to find answers. MLAI creates an opportunity for continued improvement to mitigate and eliminate discriminatory lending practices.

Risk: Machines can learn the wrong lessons from data.

Reward: Machines don’t have overt biases.

Alternative Data

AA: AI is very new. We don’t yet know how to regulate it or what its long-term impact is. As soon as data began generating, we followed this “go forth and multiply” pattern. Now we have more data than we know what to do with. Also, a lot of this data is unstructured.

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BB: Alternative modeling and alternative data are often lumped together, but that shouldn’t always be the case. MLAI alternative modeling may be used on the same data that current regression models run on and provide lift. Alternative data may be used with your existing models too but is more often used in conjunction with alternative modeling due to MLAI’s ability to handle large data sets. MLAI also has the ability to identify missing, erroneous, or wrong data and solve problems related to the inaccuracies.

AA: Alternative data, such as Facebook profiles, Twitter feeds, and LinkedIn pages, are already used in employment. HR departments use this publicly available information to determine if you are a qualified candidate. By knowing this in advance, you can change your online behavior to skew these data points in your favor. That’s the big question with alternative data in the lending space, along with privacy and transparency issues. We don’t know who gets to manipulate the data, where it comes from, or who has access to it. There’s no established system or standardized data points, which means most companies must follow their own proprietary lending rules, making it a regulatory free-for-all.

BB: While there are caveats, the rewards significantly outweigh the risks. There are many underserved individuals, businesses, and micro-borrowers with little or no credit that could benefit from alternative data. If an applicant doesn’t have good credit, or any credit at all, lenders can use MLAI techniques to paint a richer portrait about the borrower’s reliability using nontraditional factors like e-commerce histories, phone bills, and purchasing records. MLAI can open up the credit market, measure patterns, and fill in the data gaps, giving lenders a more holistic view of an applicant. Alternative data doesn’t have to be “creepy” data and doesn’t have to be social media data. Responsible and transparent use of alternative data to expand access should be encouraged.

Risk: The use of alternative data in credit underwriting raises privacy, transparency, and data integrity issues.

Reward: Alternative data can increase financial inclusion by granting access to capital to individuals and businesses with no traditional credit history.

Hackers vs. Trackers

AA: As we saw with Equifax, any time data is automated through the cloud there is the risk of data hacking. Now we are asking: who is responsible for protecting all of this data? Using such a detailed lending profile increases the necessity for data privacy and security.

BB: These are risks but the industry has always been responsible for protecting sensitive data.  The good news is, the more information we have about a borrower, the quicker we can identify errors and anomalous behavior. This is a great consumer benefit. Using the same Equifax example, imagine if we could say “this person was affected, and these actions are very different from their previous activity. This is a red flag that their information was stolen.”

Banks raise red flags when uncharacteristically large payments are made or a card is used in a different country, but imagine how much more effective these alert systems could be with additional insights into an individual’s unique behavior patterns.

Risk: More data in the cloud means a higher risk to consumers in the event of a data hack.

Reward: Additional data can identify unusual behavior quicker, which is a benefit to consumers.

The Regulator’s Dilemma

AA: Regulators have a big job ahead of them figuring out how to regulate companies using this information. Many of these companies aren’t sure how to use it themselves.

BB: Initially, users of MLAI in high stakes applications have an obligation to educate the public, create a set of best practices for their industries, and be transparent. Financial inclusion is something regulators support and this technology can help lower the barriers to entry.

AA: In late 2017,the CFPB issued a no-action letter to Upstart Network, an online lending platform that uses both traditional and alternative data to evaluate consumer loan applications. The terms of the letter required Upstart to share data with the CFPB about its decision-making processes, consumer risk mitigation, and methods for expanding access to credit for traditionally underserved populations.

By studying these companies, regulators can better understand the impact on credit in general, on traditionally underserved populations, and on the application of compliance management systems.

Risk: Regulators are still learning about AI and how to properly monitor it.

Rewards: Regulators support consumers and want to make access to credit more inclusive.

The elephant in the room: Jobs.

BB: Typically, Financial Investigative Units (FIUs) are looking at alerts 24/7, researching a person, tracking where money is going, and determining if they should file a suspicious activity report. It’s the banks biggest compliance cost and their highest area of employee attrition with numbers ranging from 15 – 35% turnover in the FIUs. With AI, FIUs can focus on stopping financial crimes rather than toggling back and forth between 15 screens and parcelling through tons of information. This should free compliance personnel up to do higher value, more rewarding work in addition to driving more efficient outcomes for their organizations.

AA: I prefer a human loan officer over an automated machine-learning system. If something happened six months ago that caused your credit to go down, you can explain that to a loan officer. How can you convey that to an automated system? Those intangibles make human interaction necessary. I believe there is something valuable in interpersonal interactions that can never be captured in a truly automated fashion.

Risk: Headcounts in certain departments that are reliant on manual processes could decrease.

Reward: New and more rewarding job responsibilities will result in less turnover, but ultimately there is no replacement for interpersonal interaction for certain positions.

Closing Arguments

BB: Currently, the industry operates with a “look back” approach for Fair Lending, which doesn’t really work. The whole process of defending and explaining discrimination after a model is put into production feels outdated. Today, we can and should build AI models to proactively remove discrimination before ever putting a model into production.

AA: This technology is still very new. Medium to big size lenders should let the technology emerge and wait to see what the regulatory landscape looks like. Regulators still have a ways to go before any of us will fully understand what the future looks like for AI in the lending space.

Now What?

Over a year in the making, TRID 2.0 was finally released on July 7, 2017. With an effective date 60 days after the final rule is published in the Federal Register, and a mandatory compliance deadline of October 1, 2018, the industry is sure to have a lot to say about these new regulations.

TRID 2.0 is meant to provide additional clarity to the original TRID rule that went into effect on October 3, 2015. Changes include:

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Cooperative Housing. Loans on cooperative housing are now covered by TRID, having previously been left to state law definitions of real and personal property.

Tolerances. New tolerances have been added and others have been clarified, including total of payments, the “no tolerance” category and good faith, and property taxes.

Rate Locks. A new Loan Estimate, or Closing Disclosure, must be provided upon rate lock, even if nothing has otherwise changed.

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Escrow. The Closing Disclosure Escrow Account Disclosures have been clarified, allowing for 12 months in “Year 1” calculations.

Additional Guidance. The amendment provides additional guidance around disclosure of construction to permanent loans, simultaneous second loans, disclosure of principle reductions, and a reiteration that re-disclosure of the Loan Estimate (LE) or Closing Disclosure (CD) is permitted at any time.

What’s Missing?

The CFPB has not yet finalized proposed changes to resolve the infamous “black hole” issue; instead, they published a new proposal. In case you’re unfamiliar, complications arise due to potential timing conflicts between the Loan Estimate and the Closing Disclosure. If a borrower experiences a change in circumstance after they have received the Closing Disclosure and needs to delay the date of closing, there are concerns that a lender will be unable to comply with both the requirements to provide a revised disclosure to the consumer within 3 business days of the change and simultaneously within 4 business days of consummation in order to reset the tolerance thresholds for the good faith determination. There is even uncertainty of the ability of a re-disclosed Closing Disclosure to reset tolerances at all. Can we expect a final TRID 3.0 to resolve the issue? Only time will tell.

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Similarly, the issue of disclosure of simultaneous title quotes for owner’s and lender’s title premiums remains unchanged and unaddressed. The current, and very complicated, method of calculating lender’s title in the case of a simultaneous quote still stands and is not currently included in the “black hole” proposal.

What Happens Next?

Our main concern after dissecting TRID 2.0 is the phased implementation. On the surface this sounds like a great thing for lenders, but what happens when a consumer compares disclosures between lenders? This gets tricky when it comes to the application date. Additionally, you don’t want to change to the new calculations in the Calculating Cash to Close table mid-loan cycle with your consumers. This would result in re-disclosed Loan Estimates, or the Loan Estimate and Closing Disclosure on a single loan may utilizing different logic. This could confuse consumers as well as investors on loan purchase, and examiners down the line.

Regardless of the outcomes our industry will adjust. One thing is for sure, policies, procedures, and technology will continue to play an essential role in mortgage compliance.

About The Author

Mortgage Marketing: How To Find Your Perfect Niche

Mortgage lenders want to rise above your competition, but they may have bigger companies and bigger marketing budgets behind them. There’s still a way to win: Truly know your niche. You can position yourself as the go-to mortgage expert for your ideal client, and you don’t have to spend more time or more money to get there. You just have to work smarter.

In today’s hyper-competitive mortgage market with fluctuating rates, low inventories, and changing borrower expectations, it is vital that you truly understand your target audience. A thoughtful, tailored approach to marketing will allow you to lock in relationships with your ideal borrowers far more effectively than your competitors.

Understanding and effectively communicating with your most profitable niche markets is critical to your success. Entire books are written about how important it is to find your niche, but there are very few roadmaps that make it easy. But without an ideal target, most of your marketing dollars will go right down the drain.

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This guide was designed to help loan originators think through the first and most critical step in their marketing strategy – figuring out your ideal prospects. The first part of the guide will explain the benefits and concepts surrounding finding your niche. The second part is a step-by-step questionnaire we call the “know your niche” worksheet. Just answer the questions and you will be ready to market very intelligently, without wasting money.

Part 1: Identify your ideal borrower

In an article entitled “How to Define Your Target Market” by Mandy Porta from, Porta states, “To build a solid foundation for your business, you must first identify your typical customer and tailor your marketing pitch accordingly.”
“Given the current state of the economy, having a well-defined target market is more important than ever. No one can afford to target everyone. Small businesses can effectively compete with large companies by targeting a niche market.”

If you’re targeting “anyone who needs a mortgage loan”, your target is too general and you will be competing against larger companies with much larger marketing budgets. You simply can’t affordably attract every potential borrower. Instead, focus on your ideal borrower.

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Don’t worry – by focusing your marketing efforts on your ideal borrower, you’re not excluding people who don’t fit your criteria. Those people will still come to you via referrals and other avenues, but your marketing program has to get specific. With a narrowly defined ideal customer, you’re intelligently targeting your marketing dollars and efforts on a specific segment that is more profitable for you or easier for you to serve.

Consider which niche markets you can serve best and you will quickly see great opportunities to focus your message with laser precision. Here are just a few examples of how this works.

Example 1: Veterans and military families

If this is your ideal borrower, you can pinpoint their average incomes, the neighborhoods they prefer, the news sources they read, where they go, and what types of mortgages serve them best. This niche market has several subsets that would allow you to get even more focused, like active service members, retired military, families or individuals. Identify your ideal borrower, and you suddenly have critical demographic intelligence that can help you tailor your marketing messages for maximum effectiveness.

Example 2: Millennial borrowers

If millennial borrowers are your ideal borrower, you can zero in on their incomes, the areas the prefer to live in, what they read, what they do with leisure time, and what types of mortgage loans are best for them. This niche market is far too broad on its own, but you can divide it further by considering gender, specific occupations and even which neighborhoods they are most interested in living.

By clearly defining your target audience, your marketing materials and value propositions can be much more specific, personalized, and meaningful to your prospective borrowers. With a very clear target, it’s much easier to determine the best values for your marketing dollars.

Yes, this is the hardest part of your marketing strategy. But we combined our expertise with the tips included in Porta’s article above to develop a worksheet that will make it much easier for you to get it right, quickly.

Part 2: Know Your Niche Worksheet

Your current customer base is important. Who are your best borrowers now? Which characteristics or interests do they have in common? Why do they come to you? Are there specific types that bring in more profitable or enjoyable business than others? Who are they? It’s very likely that other people just like these could also benefit from your services.
So, check out your competition. Who are your most successful competitors? Who are they targeting? Don’t go after the same market. You can find a niche that they are overlooking.

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Know your benefits. List all the benefits of getting a mortgage through you instead of your competitors. Next to each feature, list the benefits the borrower receives (and the benefits of those benefits). Once you have your benefits listed, make a list of people who have a need that your benefit fulfills. When you have identified your ideal borrower population, dig deeper to find smaller subpopulation niches inside of the broader demographics.

Choose specific demographics. Figure out not only who has a need for your service, but also who is mostly likely to buy it. List the following details about your niche: age, location, gender, income level, education level, marital or family status, and occupation.

Consider the psychographics of your target. Psychographics are the more personal characteristics of a population. List their characteristics regarding: personality, attitude/values, interests/hobbies, behavior. What media does your ideal borrower turn to for information? Do they read the newspaper? Do they read their mail? Or do they search online or attend events? It’s critical to understand their behavior so you don’t waste marketing dollars on efforts that your niche market largely ignores.

Evaluate your decision. Once you’ve decided on a target market, be sure to consider these questions:

Are there enough people who fit my criteria? Get narrow, but not too narrow that your population is too small to keep your loan pipeline full.

Does my target market really benefit from my specific services and expertise? Do they see a need for it?

Do I understand what drives them to make homebuying decisions?

Can they afford to get a mortgage loan?

Can I reach them effectively? Are they easily accessible?

Once you’ve identified your ideal customer and understand them, you’re well on your way. It’s much easier to figure out the most effective approach to a target market if you know exactly who they are. Think of it this way: You can throw all your marketing dollars against a giant wall and see what sticks, wasting valuable money and time with every dollar. Or you can identify your ideal borrower and more intelligently invest your time and money with precision.

The more you market to and serve your ideal borrower, the more you will know about them and the more effective your marketing approach will get over time. Remember, the work doesn’t end after you’ve identified your target audience. It’s essential to stay current on market and industry trends, know your competition, and pay close attention to your target niche. Once you’re “in”, it will be very difficult for another mortgage lender to displace you as the “go-to” mortgage expert in your niche.

About The Author

Is QC Now Officially Dead?

In 1995, with the advent of automated underwriting systems, I co-authored an article entitled “Is Quality Control Dead?” that appeared in the Mortgage Banking magazine. At that time there was a strong belief that QC was only used to find underwriting errors and with automation taking over the underwriting process there was no need to review these loans. At the time, the agencies, Fannie Mae, Freddie Mac and HUD must have been part of that trend because they made no changes to the existing antiquated QC programs they required for seller servicers.

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Unfortunately, as we all have learned to our great regret Quality Control was needed more than ever. From the turn of the century through 2007 lenders rode roughhouse over the underwriting requirements and triggered the greatest financial crisis since the Great Depression. Even as the QC Committee of the MBA meet with agencies, Congress members and consumer groups asking that they support stronger QC requirements, less and less attention was paid to QC. Despite the white papers developed showing the extent of fraud and documenting proof of what the lack of support for QC was conjuring up in the “magic elixir” that were the subprime ingredients of the collapse, QC was so weak there was no hope that the industry would listen. None of these warnings were heeded. Since then of course, QC has been revived and strengthened and the economists say we are fully recovered.

Yet once again we are hearing and reading about the latest and greatest mortgage program; the digital mortgage. According to the developers and purveyors of these programs, we have once again eliminated the need for Quality Control. These programs and their supporters claim that by using these programs have the capability of electronically validating the information entered by the consumer, running the data through an AUS and providing an approval within minutes. It is only if the loan cannot be electronically approved does it go to a loan officer to amend and approve.

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However, just as in the initiation of the automated underwriting systems, there are opportunities for mistakes inadvertent or otherwise. One of the biggest concerns is the inability to validate the information. While it sounds good, how many consumers are willing to give bank account information on-line, or those who work for small companies that don’t report the information to these on-line employment services. Sure, we can get tax returns, but they are at least a year old and not helpful in giving current income information. How is that validated?

Furthermore, despite the restrictions placed on lenders regarding DTI limitations, product and document types, non-QM loans are thriving. Just today I saw an advertisement for a “new” mortgage type, “No Income, No Employment”. There has also been a myriad of statements from the current political administration that the controls put in place to prevent another crisis will be loosened and/or eliminated in the near future.

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The question then is, can this alternative QC process that leaves numerous loopholes for bad loans to slip through and provides little incentive to do things right, stop another housing crisis. More than likely the answer is no, and because of that, it is likely that Quality Control really is dead. May it rest in peace because the rest of the industry surely won’t.

About The Author