The Future: Automated With Perfected Data

Capsilon, a leading provider of mortgage automation software, saved an estimated 5.6 million people hours collectively in 2018. Capsilon’s core technology, Capsilon IQ, uses data and AI to automate manual tasks and enable better, faster decision-making. This technology enabled Capsilon customers to realize these significant productivity gains, leading to better bottom line results while allowing them to scale quickly as volume fluctuates.

With lower mortgage originations, mortgage companies faced more competition for each loan, compressing margins and weakening business. A growing number of companies have responded by accelerating the adoption of technology, in particular for loan operations, so they are better positioned to outmaneuver competitors from a process and customer satisfaction standpoint, and make their operations more flexible to respond to market conditions.


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Drawing on their success, (left to right) Capsilon Chief Operating Officer Jim Obsitnik, Senior Vice President, Marketing Ginger Wilcox, and Founder and CEO Sanjeev Malaney discuss their vision for the future of mortgage lending.

Q: Capsilon’s mantra is “The Digital Mortgage, Perfected.” What does that mean?

 SANJEEV MALANEY:Companies are starting to automate but they’re missing a critical step. For automation to be successful, you need accurate, trusted data. That starts with the ability to effectively consume data from ALL sources— POS, LOS, asset and income aggregators, documents, etc. Then the data needs to be normalize and rationalize into useable bits of information, which feed into business applications designed to help lenders, investors and servicers reduce their cost to originate, close, purchase or service loans faster, and improve overall quality and scale as volume fluctuations hit the mortgage market.


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Q: How does Capsilon “perfect” the digital mortgage?

GINGER WILCOX: It starts with Capsilon IQ,whichis the cloud-based Digital Mortgage platform that captures and perfects mortgage data from any source and makes it useable across business applications, creating efficiencies at every stage of the mortgage lifecycle. 

Capsilon IQ captures millions of data points from digital sources and from documents. Our patented Document Recognition & Extraction technology enables companies to reduce the manual labor associated with document ingestion and management. Once documents and 3rdparty data sources have been ingested, Capsilon IQ standardizes the data and makes it accessible in as a single, authoritative record for each loan file. The source of truth for each data point and its associated evidence are always connected with the loan record.

Q: How can lenders, investors and servicers use this “perfected” data?


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JIM OBSITNIK: Companies can use the perfected data in their own systems or take advantage of Capsilon’s Digital Mortgage Solutions that use the perfected data to automate processes and solve the biggest pain points that weigh mortgage companies down.Nearly every step of the mortgage process can be automated.

Q: How does Capsilon help lenders automate their loan process? Can you provide specific examples?

GINGER WILCOX:We offer automation solutions for lenders, investors and services across the lifecycle of the loan. Right now, we’re focused on underwriting as a key area to transform for the origination channel, pre-purchase audits for investors in the correspondent channel, and loan boarding in the servicing channel.

Q: Why is underwriting a key focus?

SANJEEV MALANEY: Underwriting has been heavily impacted by the latest regulatory changes. Over the last decade, companies going from 8-10 new underwrites a day to the 1.2 underwrites a day based on MBA stats. Even just doubling that has a significant impact on a company’s bottom line, and more importantly, customer satisfaction to help retain and recruit top sales people. 


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Q:To solve this pain point, you recently launched a solution for underwriting automation. Capsilon Digital Underwriter, which helps underwriters make rapid, informed loan eligibility decisions with perfected data.  Can you explain how? 

SANJEEV MALANEY: It enables underwriters to calculate income and perform credit, income and collateral assessment using a complete, perfected data set. Capsilon Digital Underwriter runs on the Capsilon IQ platform to capture and perfect mortgage data, ensuring underwriting rules are only applied to complete, validated information. The source of truth for each data point and its associated evidence are connected with the loan record, maintaining a digital chain of evidence for each decision. This enhances the quality, security, and compliance of underwriting decisions.

Real-time listeners monitor and flag new or changed information and evidence to reduce manual checks and given underwriters the confidence that decisions are being made with the right information. The end result is a better borrower experience that gets borrowers to the closing table faster, with a more cost-efficient, lower risk loan.

Q: How important is scalability of solutions to companies in mortgage?

JIM OBSITNIK: Our customers consider Capsilon to be a mission-critical system in their tech stack, so stability and scalability are critical. We built our system to support the largest lenders in the country. Today, more than 15% of mortgages in the U.S. go through the Capsilon system each year. With Capsilon’s scalable infrastructure, our customers can scale with the markets effectively. 

Q: What does it mean for Encompass users that Capsilon is one of the first to be a part of Ellie Mae’s Integrated Partner Program?

GINGER WILCOX: As an early adopter, Capsilon is one of the first technology providers to be fully integrated into the Ellie Mae Encompass Digital Lending Platform. The integration between Capsilon and Ellie Mae allows mortgage lenders to more efficiently and securely share data between Capsilon’s solutions and Encompass to drive quality and efficiency at every stage of the mortgage lifecycle.

Mutual Capsilon and Ellie Mae customers benefit from the seamless integration that removes manual work and time delays between the systems, making it even easier for customers to leverage both solutions.

For example, Encompass customers can now use Capsilon to automate “stare and compare” activities. Companies can immediately access and compare Encompass® data to information within documents, instantly spotting where supporting documents and data don’t match, enabling them to use better data within Encompass and other business applications.

What this means for Ellie Mae customers, and our current mutual customers, is flexibility and options to take advantage of best of breed technologies, in which they can then create a technology stack designed to solve their specific lenders pain points, allow them to create competitive advantages and provide them a platform to proactively respond to the market and their customers. 

Q: What value are companies seeing with Capsilon IQ?

JIM OBSITNIK: Our customers are realizing tremendous gains throughout the loan lifecycle with Capsilon IQ, typically 300-400%. In fact, our good partners at Home Point helped us release a case study. 

The Capsilon IQ platform was integrated with a proprietary tool called Automated File Intake for Home Point’s Correspondent channel. Capsilon IQ was also rolled out across their Wholesale channel.

Home Point reduced Delegated Correspondent purchase review time by 33 percent through integration with Capsilon IQ, improving operational efficiency and delivering a better experience for its clients.

For most Correspondent lenders, the process to onboard loans for purchase review requires significant manual “stare and compare,” and companies invest in significant resources to ensure consistency across key points of data. Typically, more than 50 percent of operational staff time is spent reviewing documents side-by-side, using a checklist to make sure the documents support the data in the LOS and that the data is accurate.

Rather than adding more people to attempt to solve the problem, Home Point expanded its business, choosing to invest in building a software-powered solution, leveraging Capsilon IQ to automate manual work. This solution reduced the ‘stare and compare’ from the purchase review process and significantly improved associate productivity, decreasing file intake time.

“Capsilon has been an innovative partner throughout this process. Their understanding of the mortgage business helped us build a customized solution that boosts productivity across channels,” said Maria Fregosi, Chief Capital Markets Officer at Home Point Financial. “We look forward to continuing our relationship with Capsilon to help provide a better experience for our lender partners.”

We feel this is just the beginning of our quest to help them and others even further.

Q: What’s next for Capsilon?

SANJEEV MALANEY: Our goal is to help our customers automate 80% of the manual work that occurs throughout the mortgage lifecycle. For 2019, we’re continuing to expand functionality in our existing digital mortgage applications to help our customers achieve this goal. And, we have a few other exciting things planned, so stay tuned.

Not All Credit Scoring Models Are Created Equal

Finding a first-time homebuyer, who actually has the necessary credit score to qualify for a mortgage, is becoming more difficult by the day. According to a study published by the Federal Reserve Bank of New York, more than one-third of Americans have a credit score below 620. What is even more alarming is the CFPB’s study that found in addition to those with poor credit, there are another 45 million adults who are either un-scoreable or who do not even have a credit score.

As consumers try to deal with their credit challenges, they are being bombarded with messages about their credit scores from many different sources.  Some of these companies have even created simulated scores which many consumers find misleading and confusing, especially those who rely on those scores when seeking out financing for a new home.


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Credit Karma is one example of a company that generates scores using the Vantage scoring model (Vantage score 3.0).  Consumers frequently rely on the scores that are generated by this and similar companies before they apply for home or auto financing, only to find out that lending institution utilizes credit reports and scores that were generated from a completely different scoring model. Many people are often surprised to learn that their actual credit score is drastically different from the generated score they received online.  One reason for this is that many simulated or alternative scoring models don’t take the same information into account as the reports on which lenders rely. 

Consumer Example of conflicting credit scores: Potential borrower contacts lender and has lines of credit but DOES NOT show a score.  However, when the potential borrower pulled his credit off a website for free, he had a score in the mid-700’s.  

His specific report pulled by the lender shows NO PAYMENT FOR 8 years.


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The simulated or alternative model could be basing it on the positive payment history, were as the repositories are basing it on current activity.  A FICO Credit Score is a snapshot of what is going on today.  Over the last 8 years, nothing has been going on.  Therefore, no scores appear for this potential borrower. 

Can you picture the confusions and frustration when the lender tries to explain that this borrower doesn’t have a credit score?

It is also important to confirm that your personal information is correct with the bureaus as sometimes information is pulled in and/or NOT pulled into your report.  If something doesn’t report, it’s not included into your FICO score.   


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Therefore, It is critical to help consumers understand that not all credit scores are created equal, especially as it relates to obtaining financing for home ownership.

Here is a brief overview of different credit scoring models, the differences between actual and simulated credit scores, and the importance of knowing your actual consumer credit scores. 

FICO v. Vantage

The FICO score is a score that was formulated to evaluate creditworthiness. It is promulgated by Fair Isaac Corporation and was first utilized by lenders in 1989.  Your FICO score is calculated based upon the following five factors: 1) Payment history, 2) Credit utilization ratio, 3) Length of credit history, 4) New credit accounts, and 5) Credit mix. 


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In 2006, to compete with FICO, the three major credit bureaus developed the Vantage scoring model. This model calculates credit scores using some of the same factors as FICO, but also incorporates some additional information. The Vantage factors include: 1) Payment history, 2) Credit age and mix, 3) Credit utilization, 4) Balances, 5) Recent credit applications, and 6) Available credit. Although Vantage has been making a push in recent years, FICO scores remain the industry standard across various financial sectors for evaluating consumer credit worthiness.  

Actual v. Simulated

It is important to note the difference between actual credit scores and simulated credit scores. There are many websites, such as Credit Karma, that purport to provide consumer credit scores for free. However, consumers should be weary of putting too much credence or relying too heavily on those scores.  

A simulated score is calculated based upon actual information in a consumer credit report, but it may not necessarily reflect your true credit score, which is promulgated by the FICO or Vantage models. There are many instances in which consumers review their simulated scores prior to applying for loan or other financial product, only to find out later that they do not qualify because their actual score is lower than the simulated score. 

Importance of Getting Actual FICO Score

According to FICO, 90 percent of “top” US lenders use FICO scores when evaluating the credit worthiness of applicants. As the predominant scoring model in the US, consumer FICO scores will, more often than not, determine whether a consumer will qualify for the loan or financial product for which he or she is applying. It is imperative that consumers keep this at the forefront of their minds when devising a strategy or making a decision about when and whether they should apply for a mortgage or a car loan. 

Whenever a consumer applies for financing, and the potential lender makes a hard inquiry (pulls the consumer’s credit), that consumer’s credit score is negatively impacted, and will decrease as a result of that inquiry. If a consumer believes that he or she will qualify based upon the simulated score, but is later denied, their credit score will take a hit unnecessarily. 

Because of the deleterious effect that hard credit inquiries have on a consumer’s credit profile, it is imperative that consumers know their actual credit score prior to applying for loans. There are companies that offer monthly subscriptions, which include actual consumer FICO scores that are updated monthly. This type of service is invaluable for those who are serious about achieving and maintain credit health, and eliminating any guesswork when applying for loans.

In addition to accessing actual credit score, here are some ways in which consumers can build and/or improve their credit profile.

Two quick way’s to create a score:

Start using a credit card, if you don’t already. Using a credit card and paying it on time every month is a great way to begin establishing credit history.

For those accounts that are open, make sure to use them periodically.  If you don’t use them, the creditor might close the account down which could have a negative impact on credit score.  

Why do these two ways impact ones credit:

30% affects Utilization. It is best to have several accounts with low balances distributed then it is to have fewer accounts maxed out. To figure utilization: Balance (divided) by Credit Limit = percentage. Lower than 10% recommended per account, this is one of the fastest means for increasing the over all credit score.

15% affects Established History. The longer you maintain open accounts with creditors the better. When first starting out of course this is not easy; but this is where getting added as an Authorized User to another persons established credit comes in best. Remember that the contributor must have an account that has long history; clean payment record; high credit limit, and low balance. Also need to check with the creditor to insure that they have a policy to report authorized user accounts to all three major credit-reporting agencies. Anther great option is getting a secured credit card that reports to all three bureaus.  Try to find options for secured credit cards that do not require to pull credit. 

SPECIAL NOTE to quickly build accounts: Authorized user accounts are the best way to go; since you are not legally responsible for the debt rather than Joint or Co-Signer accounts. Also, if this account starts to report negatively; these accounts are usually easier to remove from the credit reports by either contacting the creditor or requesting termination of the relationship; or disputing through the CRAs.Just because you can pull a score off the Internet does not mean that it is the score that a lender will use to qualify you for home financing.  Remember, not all credit scoring model are the same, especially as it relates to the mortgage industry. 

About The Author

Bringing Back Profitability In Lending

In today’s mortgage market, lenders are struggling with constantly changing rates, rising LO compensation, low productivity, and margin compression.  With paper-thin margins Mortgage Bankers are looking for solutions that will help turn the profitability tide.

One of the main barriers for lenders as they look to address these challenging market conditions is their inability to easily access data across multiple systems and sources to make timely and informed business decisions.


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What they need is a dynamic way to easily create reporting and analytics through access to the vast array of information in their LOS, general ledger, hedging and servicing systems.  Lenders are not looking for more data.  Mortgage Bankers needs a single platform that absorbs all data sources and provides analyzed visual data of the entire organization near real time to gain profit intelligence. 

Mortgage Bankers would benefit tremendously from a solution that converges the mortgage banking loan origination system, general ledger, payroll, contact management, warehouse, quality control, secondary marketing, and servicing data to provide a complete picture of their lending operation, with focus on providing the insights needed to manage differently while driving profitability.


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Leveraging all the data from multiple sources allows Mortgage Bankers to make well-informed decisions in real-time. The ability to identify and eliminate performance problems, waste, and revenue leakage is crucial, especially in today’s challenging lending environment.  Bringing profitability back to lending requires close attention to these key and detailed metrics.  

For example, it’s just not good enough to measure loan officer performance based on production volume once a month when you calculate commission. To effectively manage a sales force, lenders need to measure loan officer profitability, down to the loan level.


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By measuring revenue and compensation, and then calculating contribution margin at loan level, lenders can see a clear picture of a loan officer’s contribution to profitability. By consistently stack-ranking sales people, sales, teams, channels, and branches, Mortgage Bankers can see patterns more quickly, and take steps to respond to them to gain a competitive advantage.

It’s not enough to simply see the scoreboard. You need to dig deeply to see the actual patterns. For instances, if a lender had several poor-performing branches.  Before deciding to shut them down, it’s important to identify loan officer performance and seek options to cull the weak performers without abandoning the handful of solid performers.


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Once they identify most profitable loan officers, they need to ask themselves which product gives the best return and which branch is creating the most opportunity for the product. How do they find an answer for this? For sales, volume and revenue are key views. For operations, turn times matter. For secondary, gain on sale, SRP are important, but so are time to fund, investor suspensions, and warehouse dwell time. 

Everyone tracks operations caseloads. Do you know with certainty which processors turn profitable files most quickly? Can you identify your current best performer at a glance when a production spike has you scrambling to assign loans? Do you know which loan officers get great service from underwriting, and why? Can you see which branches are making it happen, and which may need help this week? Do you understand the connections among profitability, turn times, credit standards, and your operations team?

If you can’t answer yes to each of these questions, you are likely relying on gut feelings and one-dimensional views of your business when you make important decisions about compensation, workload assignment, and process improvement.

The key is being able to identify whether profit, volume, mix, productivity, cash flow, secondary gain, loan servicing metrics and any other key metric are on target, near real time with one click.  Determine how good is your data? Identify data integrity issues and dirty data near real time with one click.  Reduce costs by identifying sub-par performance by product, department branch, and channel near real time with one click.

Up until now, easily gaining access to this information across multiple systems and resource was a daunting and ineffective task, significantly limiting a Mortgage Bankers ability to gain profit intelligence.

In today’s highly competitive mortgage market with fluctuating rates, increasing cost to originate, margin compression, and heightened competition, understanding lender, branch and individual LO profitability is critical. Teraverde’s Coheus Profit Intelligence is the first solution of its kind that absorbs all data sources and provides analyzed visual data of the entire lender’s organization near real time. 

This allows the lender to take this actionable intelligence and make swift business decisions to gain a competitive advantage in the marketplace. 

With applications like Coheus, effective management teams can watch for patterns by analyzing data. This is done by listing lender credit by branch, loan officer, product and other factors, patterns emerge that can be investigated and turned into action to correct bad practices and reinforce effective ones.

As seasoned industry executives, we have seen and worked through major challenges in the mortgage lending and banking industries. We know what works and what doesn’t. Our experience allows us to accurately identify the appropriate business solutions the first time, transforming lender profitability. 

We specialize in increasing profitability by identifying the most profitable products, loan officers, branches and channels. Identify whether profit, volume, mix, productivity, cash flow, secondary gain, loan servicing metrics and any other key metric are on target, near real time with one click.

With our enterprise profit intelligence platform, high-powered industry insights, superior workflow management, robotics process automation, and visual classification, Teraverde clients have experienced a significant reduction in costs, and increased performance, while bringing back profitability in lending.  

Coheus goes beyond cost per loan – Coheus lets users look at revenue, costs and profitability per loan by product, loan officer, channel, and branch.  Also how long it takes for each step in originating a loan, and identifies variations among employees, departments, and branches.  Along with looking at the credit box, employees, channel and branch for loans that default or pay off unexpectedly.  Coheus helps model and explore the possibilities of channel, product, funding, process and technology innovation.  It provides profit intelligence that can be used for constant improvement of process and profitability.

Coheus drives Mortgage Banking profitability one lender at a time. Here is an example of Coheus in action. A Mortgage Banker was alerted to a spike in delinquent loans, took action, saving $4.2 million of delinquency and repurchase costs. 

Another Mortgage Banker reduced time to close by 16 days, reduced # of missed scheduled closings to less than 1%, reduced hedge costs by $2 million, increased daily underwriter loans underwritten by 40% and improved customer satisfaction by 10%.The time is now to bring back profitability in lending.

About The Author

All Arrows Point in This Direction!

As I have this bird’s eye view from convention hopping to where the industry is heading, I am hearing, through objective listening several things. First, everyone has solidified, through discussions, that the mortgage industry is heading to a more digital world and that evolution is carrying people to new places.  

Every major 2019 convention to date has confirmed that to be true, in fact more time has been spent confirming and debating that “yup things are changing” than discussing the destinations that lie ahead for all of us.  


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I have listened to statistics that are undeniable. More millennial job entry, more mobile application adaption, more technology, more social media, more Non-QM, more Niche-ing and just more of what we all have seen predicted. And as I have said…the train has left the station.    

So, we know where it’s headed, we know ultimately the mortgage industry’s social media buzz is a replica of the country’s political divide, but in our industry the great divide is “tech or no tech” and we also know that Mortgage Loan Originators are paying attention to where the arrow is pointing. If not because of the buzz, but because of their thinning wallets.   


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Margin compression, inventory issues, seasonal decline and rising interest rates have given way to “more work for less money” which is nobodies idea of a motivational plan. That said, MLO’s will always survive, that is what they do in the many ways they solve to these problems. In this world of angst and uncertainty, the leaders in our industry are tested, the business developers and recruiters need to be on point and all hands are called to the deck.   

 So, allow me now to create organization from all this chaos. I have resisted but eventually waded into some social media discussions and had a few flailing hands hit me in the head, but held my own on the topics confirming technology evolution to all the naysayers, so trying to do my part. Also defensive of the same naysayers that seeming throw cold water on every great idea that puts the old school mentality in some form of discomfort, but too bad. We must be agents of change now. The world is changing, not just the mortgage industry. 


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What I think is happening truly is not up to debate and much like political debates I also don’t think opinions are driving the direction of this. I don’t think sharp-tongued speakers will convince loyalists of a new direction. However, I do think those thin wallets might make people take note to their surroundings. That is why the victors of this year’s mortgage industry will be those who remain steadfast and sharply focused on their businesses and not all the shiny objects flashing in their peripheral. I think they need to go get educated. If you are an MLO in this industry and you have not signed up or committed to attending a conference, then do it. The one thing all these awesome convention hosts have in common is bringing real and diverse voices to their platforms with an ability for originators to engage, ask questions and walk away more informed. 

“NEXT STOP”!

So, one such conference just occurred pulling 1,000 MLO’s all the way to the sunny state of CA in Irvine for the AIME Workshop, Association of Independent Mortgage Experts (AIME). That is an amazing level of attendance really for an association that is under 1 year old. At the helm of this organization, Anthony Casa, who I sat down and interviewed, as well as several media that attended for an unbiased opinion so that I could tell all of you avid readers of TME, where to truly focus on getting informed this year.   


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I should note that prior to sitting with Anthony, we had not personally ever spoken one on one. Obviously we were very aware of one another in the mortgage industry, we had no mutual cause of monetary affect (I feel the need to say) other than a shared love for the mortgage industry and finding ourselves on similar personal trajectories in our careers, both having left the helms of our prior companies, forsaking the literal work for leadership and the cause. Over the years, I had heard “things” about Anthony, like he is “controversial” or “broker only focused” and that was completely untrue of both my personal experience in talking to him and by the repeated perception of those objective media representatives. We will get to them.  

Search Parties! 

Yes, I could tell early on, Anthony Casa is not in need of having to say things for popularity however I found him to be very authentic and honest, a genuine person. He is also polite, professional, clearly experienced and poised. He is most of all believable. As a sales leader, or as sales people go, we aren’t easily “sold”. Like most leaders I suspect in his authenticity he has said unpopular things, albeit true. I asked the hard questions, what he stood to monetarily gain by developing the AIME convention and in his own words: “Honestly, I hit my financial goals in life at some point and now I am leading with cause and know the money will follow”. He cited a lack of industry leadership and a true need for culture.  

As AIME’s popularity has grown and its following increased, Anthony finds himself in a place where his average post is getting 30,000 views so clearly, the haters and the admirers both are listening. When you get that kind of attention, you are holding a microphone that surely will continue to attract and more over you are doing and saying a lot of things people want to hear. I think in asking endless questions he clearly does understand his position and his responsibility of this mentorship. 

AIME’s Irvine Workshop was made up of 80% broker mortgage originators and 20% lender MLO’s.  That means the platform is attracting more than folks from his personal background running a thriving brokerage. Josh Pitts, Founder of Shred Media attended with his colleagues from the ‘Industry Syndicate’ team, Jason Frazier Podcast company that now leads the mortgage industry in the most syndicated independent mortgage podcasters under one roof, also two people who spoke at Agent 2021 of Gary Vaynerchuk in Miami, who go where the wind is blowing. These guys are showing up where the buzz is at and covering these events. On hand in Irvine for AIME, when I asked Josh Pitts, he said what stood out for him was the sheer sense of “community and culture”. When asked for an honest review Josh said he believed it was “One of the most powerful gatherings of Mortgage Loan Originators” that he had ever been a part of. By sheer numbers I could see from thousands of miles away how the quantity of this gathering would heed respect to its collaborators. Jason Frazier the Industry Syndicate Founder told me when I asked about AIME, “There is a true professional community being built where competitors are coming together to share tips, tricks, and tactics. The energy and excitement are unlike anything I have ever experienced at mainstream mortgage industry events.”

Culture Counts!

Anthony in fact touted “culture” as the thing most eroding in our industry right now right in front of our eyes in this “imperfect time in history” he sighted originators are seeing culture erosion as margins thin with owners unwilling to sacrifice their own margins for exposing “fraudulent cultures. “A statement probably very unpopular but also very true. Of course, we could argue the costs and overhead of companies trying to right size in this market are showing reluctance for out of job preservation of its own teams. More obvious is that the originator who holds the sales reigns to these companies are sharply focused on where that wind always blows. Anthony is right, in this case, serving to the front line of the mortgage industry, there is a tail wind of independence that need not be ignored.   

I am not easily swayed by people, I will add. I owe nothing to Anthony Casa, in fact, I have worn a different teams colors for the better part of my career, still we speak the same language and I believe he truly is trying to help originators find their way in a world where leadership is certainly called upon. A person who might have once found himself on the heels of this industries opinions, he was pleasantly un-defensive. Funny thing that happens when your primary focus truly goes to leadership and honest mentoring. HIs belief is “ if you work really hard and pour yourself into your work that money and opportunities will follow, it will all work itself out in the end, but it is not my current focus. “ 

The 911 

For information purposes for readers, I offer that AIME Fuse Conferenceconvention will be held in Las Vegas on October 12ththis year with some heavy hitter speakers on the venue and maybe someone with the initials GV in tow, there stands to be a lot of attention. Workshops including the Fort Lauderdale FLA being held on April 17thalso stand to pull in local and east coast originators wanting to again sit down and learn more for themselves and the directions they all need to focus on. 

I spoke to Clayton Collins, CEO of HousingWire and asked him for a statement on AIME, where he had attended to spend time with industry leaders and clients. Clayton said, “The most interesting theme occurring in the housing industry today is happening where loan originators, real estate agents and homeowners intersect. I have massive respect for originators proactively collaborating to build their businesses and help the homeowner. There’s a level of collaboration going on in the AIME community that is truly unique and that extends beyond the mortgage broker. Consumer direct leaders, technology entrepreneurs and retail lenders were sitting side-by-side with wholesale lenders talking about the future of loan origination. At the end of the day attendees walked out of Hotel Irvine with new relationships and ideas, but more importantly, they appeared energized and hungry to get back to work serving homeowners and their referral partners.” 

Where is YOUR arrow pointing?

In ending I will leave you with a quote I chose that seems relevant to this topic, from a book Anthony Casa quoted as a great read, that I surely will be picking up.  ‘Relentless’ by Tim Grover, “Ask yourself where you are now. And where you want to be instead. Now ask yourself: What are you willing to do to get there?”    There in lies the answer to where each one of our arrows are pointing and whether we are following its obvious direction, or moreover putting in the time to figure it out. 

About The Author

REVOLUTION!!!

Being touted as the answer to all the stresses and dissatisfaction currently found in the workplace, it is being developed as the advancement promised by technology prognosticators who have promised that work can be reimagined to be more flexible, faster and adaptable. A benefit, or so we are told, is the elimination of work that is standardized and repetitious.

So, is this good for mortgage lending?  Reading numerous articles in industry trade magazines and discussing these ideas with those who are currently mortgage lenders, it is apparent that we actually know very little about AI. Every article I have read claims to have found the answerandgives us a short, simplified explanation about what it actually does.  To add more confusion, artificial intelligence technology is sprouting a completely new set of acronyms which are anything but helpful unless you thoroughly understand it.  Another issue I found prevalent in the discussion is the fear about its usage and the elimination of jobs we now hold. But are there any risks in using AI that we don’t know about?  Do we understand how technology can make better decisions that humans?  What do we need to have to make sure the technology works accurately?  How can we implement it into our production and servicing processes?  So, before we rush head-long into the next great thing, we need to take the time to really understand what this technology is and does. 


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This series of articles provides some basic definitions utilized by artificial intelligence technology providers, identifies the various iterations now in use and describes what critical elements are necessary for it to do what it claims to do. In addition to the technology itself, the articles will focus on the risks and opportunities associated with AI as well as discussing the potential for process and job function disruptions the industry will face as it is implemented. 

Beginning with the basics

“Work”, the basis of economic betterment, is changing again.  Known as the “Human Economy”, work involves people performing activities that are considered economically productive.  From the earliest days of economic activity humans have experienced the need to improve productivity.  Work, as we think of it today began with the development of wheels, wagons and animals for transportation as well as the use of small hand-tools for creating individual products one at a time. Next came the industrialization of product production, and then the initialization of automation to conduct the actual work. Ultimately this has led to better products, more satisfied customers and greater profitability while providing a better income and more time for leisure and family time for employed individuals. We are now in the initial stages of the next advancement, the use of artificial intelligence, to once again change what work is and it isn’t. Despite numerous nay-sayers, this new technology is bound to have a significant and fundamental change to our business. We, as an industry, need to know more. 


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As defined by Paul Daugherty and James Wilson in their book, Human + Machine, Reimagining Work inthe Age of AI,artificial intelligence is a system that extends human capability by sensing, comprehending, acting and learning.  In other words, it is the simulation of intelligent behavior in computers or sometimes referred to as a machine with human cognition and the ability to carry out tasks as a human would. 

Within this field there are various levels of “intelligent” program types. They have names such as Expert Systems, Machine Learning, Deep Learning, Robotic Process Automation (RPA), and Neural Networks. Another common acronym describing how AI works is Natural Language Processing. All of these terms reflect a variation on the basic purpose of AI, that of having machines do the work of humans.  But how it is done and what functions it addresses are quite different.   


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Defining Types of Artificial Intelligence

Today, the term is discussed by many in our industry as a single effort of implementing AI, yet they confuse terms like Expert Systems, Machine Learning and Deep Learning, seeing it all as one new technology.  When you hear these buzzwords tossed around in conversations, it is obvious that many do not recognize these terms as very different types of AI.  In order to clear up the confusion a definition for each type must be recognized for what it does and an understanding of how it can be used, beginning with simplest to the most advanced.  

All artificial intelligence products are based on one core requirement; the ability of the system to collect and learn facts.  Just as individuals are not born with the knowledge they have today, a machine must learn what it needs to know.  First these machines must be taught the basic facts. Even once these basic facts are learned, they are not innately able to associate those facts with the problem presented to it. It must be taught how to associate these facts appropriately with the problem it is trying to solve. As the complexity of the problem increases, the need for these machines to conduct this association becomes more complex, thus the varying levels of AI. 


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Because AI is a relatively new technology, scientists do not necessarily agree on the terms and definitions utilized in describing the capabilities of current AI products.  The definitions and examples given below are most consistent with the terminology we use today.  In addition, there are terms that are frequently used within the scientific community for describing the abilities of specific AI functionality.  

Expert Systems– The most basic of AI products, this technology is a method of automated reasoning based on a very specific set of facts, rules and principles.  The automated underwriting systems we use today are an example. When we ask a question, such as does this loan meet our credit guidelines, the program takes the facts as provided in the application and from external data, compares them to the facts taught to it as an acceptable loan and filters this data to arrive at an answer. 

If any of the data is inconsistent with the “facts” taught to the machine, or there is no rule, it will be unable to decide.  These systems do not “learn”.  For example, if an AUS system has a rule that limits DTI ratios to 43%, it will not approve one at 44%, regardless of the fact that the human who then reviews the application does so 95% of the time.  The system has not “learned” that 44% is acceptable.  

Robotic Process Automation-RPA was designed and is utilized to automate those processes that are routine and labor intensive.  Today businesses find that work associated with repetitive tasks, such as inputting data, making calculations and answering standard customer questions is work that can be done by basic RPA technology.  Your home-based Alexis system is an RPA devise that answers questions and conducts some limited analyses based on the input.  For example, when you ask Alexis to play music, it will find a music program and begin to play it. The robot has learned what music is, the types of music and what performers are associated with each.  If you do not like the type of music selected you simply tell Alexis and the music is changed.  The same applies to individual songs.  Alexis then “learns” what type or piece of music you do not like and will not play it again.  The “bot” as it is now called, has learned something new and will apply it in the future.  

Today, companies with workflows that are consistently repetitive and simple are using this technology.  For example, a warehouse which contains thousands of products which need to be compiled into one order uses these bots to find and deliver the items to a central location.  These bots, which have the appearance of what we think of as robots, move up and down narrow rows of products and quickly and accurately collect the necessary items. This has resulted in the elimination of personnel who perform this function with much less accuracy and in a greater time period.  It even has the impact of allowing warehouses to be built higher, thereby eliminating the need to have long, low buildings with lower rows of goods so that humans can reach.  

One of the critical features for these bots is the ability for it to recognize what the user is saying in their own vernacular. Known as Natural Language Processing (NLP), its purpose is to allow bots to learn various languages, accents and idioms used by customers. The development of NPL requires that this occurs for industry specific terms as well.  Asking a question of a bot when the terms are used in different scenarios will most likely not get the answer you need.  Again, if the bot has been trained in the Northeast and is asked a question from someone in the South, without NLP adaptation to this accent, it will have problems answering the questions. 

Narrow A.I.- This term has come to be used by many of the individuals working in this field. Like its name suggests, it is focused on executing a single task.  Human interactions with a narrow A.I. are limited because Narrow A.I. can’t think for itself. This is why sometimes you’ll get a nonsensical answer back when attempting to use it because it lacks the ability to understand context.

General A.I. General A.I. or Strong A.I., as it is sometimes called, provides the ability to understand context and make judgments based on that context. Over time it learns from experience and is even able to make decisions, even in times of uncertainty.  Even with no prior available data it can use reason and be creative. Intellectually, these computers operate much like the human brain. This is where we are headed when we talk about its functioning in place of a human.  To understand the abilities of this technology and how it operates, the basic functioning of the human brain needs to be understood.  

Neural Networks. Each individual has within their brain a series of networks which transmit data. This can be a s simple as learning what tastes you like and what you don’t like.  Before you learn, by tasting, that you don’t like fried liver there is nothing in your thought processes that tell you it is not acceptable to you.  However, once you taste it and realize it tastes awful to you, you reject this food choice because your brain has learned from this observational data.  Our internal neural network processes the data we are observing and alerts us to the fact that fried liver tastes awful to us and alerts us to that fact before we make an unacceptable choice.  

Developing these neural networks in our brains takes time. My son recently bought a 2-month-old puppy.  Obviously the first thing he needed to do was house train him and so he has spent a great deal of time making sure Bogey understands what is expected and what he must do when he needs to go.  Developing this neural network in the dog’s mind is not an easy task.  Over time, the training took hold.  In other words, a neural pathway had been developed. 

Machine Learning. Machine Learning, “ML”, technology. This is the field of computer science with algorithms that learn from data that is “taught’ to the technology.  It also uses the data and incorporates algorithms that learn from and make predictionson data.  This technology can learn from humans or it can learn from other data. In other words, this technology is conducting some of the analytic thought used in bringing various components together and allows it, to some extent, to predict a result.  Another utilization of ML is known as “supervised learning”.  In this scenario data is broken into categories such as inputs and outputs and humans use it to develop an expected output from the technology. When the output is inconsistent with what is expected based on the algorithm, it sends out an alert to the user.

One of the most common uses of Machine Learning is found in fraud investigation. In these cases, the machine is feed information and searches for a pattern of data, such as spending habits or income, and utilizes its algorithmic tools to determine if the data is what would be expected.  If in using the previously received data, it determines that the new data does not fit the pattern the output reflects this inconsistency and potential fraud is identified. This is what happens before you get that phone call asking if you had made a recent trip to Saudi Arabia. 

Deep Learning. Deep Learning specifically refers to the ability of the machine to learn from other data. Deep Learning consists of a multi-layered network of algorithms in which data is processed through multiple layers with each layer as individual inputs.  It also allows the data to flow back and forth between these layers thereby expanding the systems knowledge base.    Deep Learning “DL” machines can analyze patterns and people to identify potential problems or opportunities far enough in advance to allow for early intervention or resolution.  Imagine the ability to know the probability that a borrower will default even before the loan has closed and been set up in servicing.  

These types of artificial systems, machine and deep learning, are both predictive systems. These systems find relationships between variables in the historical data, identify a pattern and then develop a model to predict future outcomes.  Developing these patterns requires the use all available data, including borrower information from sources other than the application, property information, both local, state and national, economic conditions, etc., that are now available provide the opportunities to find correlations never before considered.  By understanding these different approaches to artificial intelligence, it is much easier for management to evaluate the type needed to successfully implement such a program.  There are however other issues to be understood and addressed before taking the leap to artificial intelligence.  The next article will explore the risks and opportunities of AI along with new developments addressing these issues.  In addition, it will discuss what it means to “reimagine” how work will be done. Finally, we will discuss what a reimagined mortgage operation looks like and the impact its inclusion will have on the workflow and job functions.  After all, don’t you want to know if a robot will be taking your job?

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Think About Adding Value

In covering the mortgage space for many years, there are always partnerships to report on. That’s great, but when these companies join forces, I thin they should first think about how this partnership really benefits the lender.

For example, Floify, a mortgage point-of-sale solution, has joined forces with Plaid, the technology platform and data network powering many of the largest and fastest-growing applications and businesses in financial technology. The partnership enables lenders and loan originators to order and receive Plaid’s Asset Reports from the Floify point-of-sale solution, simply by having consumers connect their bank account through Plaid.


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Once integrated with Floify, Plaid can be configured to automatically trigger a request for borrower asset reports upon the conversion of a prospect into a loan file, or manually trigger from an active loan file. After a Plaid request is initiated, borrowers are prompted to select their financial institution and enter their credentials via Plaid’s front-end module. Upon successful login, the borrower’s asset report is securely transmitted and synced to their corresponding loan file, which saves valuable time in the loan origination process.

“Floify is thrilled to partner with Plaid as we continue to use our automation technology to improve the mortgage process for loan originators and borrowers,” said Dave Sims, CEO of Floify. “Our integration with Plaid further simplifies and accelerates loan origination for mortgage professionals who combine the power of Floify point-of-sale system with Plaid’s Day 1 Certainty-approved digital asset verification functionality.”


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Floify simplifies the way lenders collect, verify and manage loan documents; track loan progress; and communicate with borrowers and other loan stakeholders. With Floify, mortgage professionals have reported saving hours in the loan origination process, while increasing the profitability of their lending operation and improving borrower satisfaction.

Floify is a digital mortgage automation and point-of-sale solution that streamlines the loan origination process by providing a secure application, communication, and document portal between lenders, borrowers, referral partners, and other mortgage stakeholders. Lenders use Floify to collect and verify borrower documentation, track loan progress, communicate with borrowers and real estate agents, and close loans faster. Floify is based in Boulder, Colorado. 


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Plaid is the technology platform and data network providing the tools and access needed for the development of a digitally-enabled financial system. Plaid makes it easier and safer for developers—from the smallest startups to the largest financial institutions—to build innovative financial services and applications. Plaid’s infrastructure makes it possible for companies like Robinhood, Acorns, Betterment, Coinbase, Venmo and hundreds more to serve their customers, regardless of where they bank, allowing them more insight and control into their spending, investing, budgeting and their overall financial well-being. Today, one in four Americans with a US bank account use Plaid.

Similarly, Beta Music Group Inc. through its operating subsidiary Get Credit Healthy, Inc., afintech platform that provides independent mortgage originators with credit resources, education, data intelligence and lead recovery has partnered with ARIVE, a platform that offers the first of its kind mortgage marketplace designed to allow independent mortgage originators access to lenders, borrowers, and third-party vendors in a seamless ecosystem.


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Through a partnership with AIME, the Association of Independent Mortgage Experts, ARIVE will provide independent originators with the connections and tools to both compete in a crowded marketplace and serve increasingly tech-savvy borrowers nationwide.  Lenders and third-party providers want to make it easy for their customers, and AIME is over 35,000 strong. 

ARIVE has multi-year contracts with a network of more than 20 wholesale lenders. That includes five of the top ten wholesale lenders in the country: United Wholesale Mortgage (#1), Caliber Home Loans (#2), Stearns Lending (#3), Flagstar Bank (#7) and Home Point Financial (#8). Combined, these lenders make up nearly half of wholesale market share. Top Renovation Lender AFR Wholesale, Reverse Lender Finance of America Mortgage, and Paramount Residential Mortgage Group (PRMG) are among the additional 20 wholesale lenders connecting to ARIVE.

Elizabeth Karwowski, CEO, stated: ” We are extremely excited to partner with ARIVE to deliver one-click access to a host of credit services and solutions to assist the ever growing number of Independent Mortgage Originators on the ARIVE platform.”

Today’s fiercely competitive financial services market challenges originators like never before. Heightened pressure to create new loan opportunities, reduce prospect lead fallout, and provide better pipeline visibility poses a significant burden on independent mortgage originators.

To thrive under these market conditions requires a revolutionary new solution that transforms a currently untapped market into a well-qualified, well-informed applicant pool. Get Credit Healthy converts fallout into funded, helping independent mortgage originators close more loans while providing them with a significant competitive advantage.

ARIVE, LLC., is a private technology company based in Philadelphia, Pennsylvania. Conceived as an engine to drive mortgage technology into the future, ARIVE offers the first of its kind mortgage marketplace designed to allow independent mortgage originators access to lenders, borrowers, and third-party vendors in a seamless ecosystem.

BEMG, through its operating subsidiary Get Credit Healthy, utilizes its proprietary processes, platform, and software to integrate with lenders to make it easier to recapture leads. Developed for and by those with extensive experience in the mortgage industry, Get Credit Healthy’s platform has already facilitated over $200 million in new loan opportunities.

Get Credit Healthy has showed sustained growth over the past three years and shows no signs of slowing down. Get Credit Healthy is working to increase its network of partners and is looking forward to a very promising future.Why do I bring up these partnerships? Because they make sense. Both are trying to help lenders solve real pain points. That’s what good partnership should do. As I continue to report on this industry, that’s what matters most. Doing something positive for lenders that matters is what makes for a good partnership.

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Driving Down The Cost To Originate

Attend any mortgage industry event or trade show or read any of the industry publication, and you will hear people talk about the rising cost to originate, margin compression and declining profitability.

Lenders continue to struggle in an ever-changing mortgage rate environment, reporting negative profits for the first time since Dodd-Frank compliance brought down profits in 2014.


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Independent mortgage banks and mortgage subsidiaries of chartered banks reported a net loss of $118 per loan originated in the first quarter of 2018, according to the MBA’s Quarterly Mortgage Bankers Performance report. This is down from a gain of $237 per loan in the fourth quarter of 2017.

“In the first quarter of 2018, falling volume drove net production profitability into the red for only the second time since the inception of our report in the third quarter of 2008,” said Marina Walsh, MBA vice president of industry analysis. “While production revenues per loan actually increased in the first quarter, we also reached a study-high for total production expenses at $8,957 per loan, as volume dropped.”


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So how to we drive down the cost to originate and bring back profitability in 2019?  It starts with asking some tough questions and looking outside of the normal this is how we always do business answers, if we are going to come up with some sustainable answers.

Can we afford to continue doing business as usual?

Is there a better and more efficient way to originate loans?


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How do we increase origination volumes without blindly hiring more LO’s?

How many loans does the average LO close a month in your organization?

How many loans can a processor per day, month, and year handle in your organization?

Ask the same question about your Underwriters? Closers? Funders? Etc.?


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Lenders are notorious for running tons and tons of reports.  Unfortunately, reports become stale the minute you print them, so you forward-thinking lenders have moved to real-time dashboards. While that is a step in the right direction, that’s only half the battle. The real key is— what do you do with that data?

Why is it that the average underwriter could handle a pipeline of 100 loans pre-crash but can’t handle much more than 30 today?

In taking a hard look at the numbers, it is very clear that you can’t continue to do business as usual and expect to turn the tide against the rising cost to originate.  The key is improving operational efficiency. The challenge is how we put this into action.

It is critical that if we are going to defeat the villain, we must take the time to not only understand how much we are spending on each task to originate, but also truly understand how we can become more efficient.

It is one thing to understand the data, but if you want to truly gain operational efficiency and drive down the cost to originate, what you do with the data is so much more important.  Is the data telling you where the bottlenecks exist in your origination workflow?  

Those bottlenecks/inefficiencies are costing you money and contributing to your rising costs. Once you identify the bottlenecks, how can you eliminate these bottlenecks through workflow automation to create consistent processes that streamline and reduce costs?

Let’s take a step back and look at history. When Henry Ford implemented the assembly line, they saw a dramatic increase in productivity, here’s why:

Work was prioritized, pushed to the right person at the right time

Ford created sub-assemblies to maximize output

Technology then automated the items that a system could handle, but people still do a majority of the work today. It’s more of the right person, at the right time, and at the best price.

Consider this— you’ve been successful thus far. You’re closing loans, and you might be somewhere in the middle when it comes to profitability. Now, if you could only get the most out of every motion in that process…

The first thing we can help you do is Identify. Zooming out of the day-to-day can work wonders, especially when done by a fresh set of eyes. Here’s an example of questions you might ask in identifying key areas for improvement.

What is our process for gathering borrower conditions?

How do you actually Track, Approve, and Reject documents?

How much of this is done via email?

Do all interested parties of the transaction have a Real-time Status into each one of these conditions?

For example, say we’re waiting on an item from a third-party. Do we know how long we’ve been waiting for that particular item? Is it stopping someone else from performing an unrelated function? What does the follow-up process look like? Are we just emailing for updates? 

Once we’ve identified the key areas for improvement, you’ll have a better understanding of how you might transfer responsibilities from one employee to another. Think of it like this— a high-cost resource should almost NEVER perform a low-cost function. If it can be handled through automation, even better! 

The next thing to identify is Communication. So much gets lost due to a lack of transparency. Systems were designed so that multiple users can’t have edit rights to the same areas. It makes sense. If someone is reviewing income and someone goes in and changes the income… well…

As you identify these key areas that need to be communicated to multiple people, you will begin to uncover missteps that create vicious cycles of he-said/she-said. A flurry of CC and BCC emails ensue, and this leads to, well…a lot of bad. 

We can help you go from “CC and BCC everyone just in case” to pointed communication at the right time to the right person. This way your team is being communicated to/with on a “need to know” basis.

You no longer have to be a victim to the rising cost of originating loans. Allow Lodasoft to help you rethink how you are originating so that you can streamline your processes while reducing the cost to originate. Let operational efficiency become the hero in your organization.A team of lenders and mortgage technologists created Lodasoft. We’ve been on your side of the fence—struggling with the day-to-day challenges of the constantly shifting mortgage process and rising cost to originate. Based on that experience, we strive to make lenders more efficient, scalable and profitable.

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The Race To Inspire

We all know content marketing moves the needle on online lead acquisition. When it comes to interesting content, however, some industries have a tough time getting away from their stodgy image. As a general rule, for example, you’d expect more cool content from a soft drink company than a B2B software firm. In fact, B2C tends to beat B2B in general, at least in theory.

The exception to the rule: B2C financial services. In the article “8 Awesome Content Marketing Examples In the Financial Industry That Will Inspire You”written by Rob Steffens, he says that companies in the financial services industry have one of the most buttoned down and knotted up images of any industry.


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And yet, banks and credit card companies can succeed with inbound content marketing just as well – or even better – than the average brand.

Why? The answer is simple.

More than anything else, content marketing is about educating your audience. The best content marketing examples involve teaching people about a subject in a new way. Good content sparks interest, which enhances retention and fosters rapport between visitors and your brand.


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Marketers in the financial sector need to craft their content with care thanks to strict regulations. Still, they have the huge advantage of being able to educate their consumers on subjects that most people find mysterious. That makes it easier to position your brand as a trusted resource that makes life easier.

Even having said all that, it might be hard to imagine how content marketing in finance works. Luckily, some financial firms have put out stellar content marketing examples to learn from.


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Let’s dig deep into some of the top content marketing examples in finance!

1. Transamerica Wins With Content on Facebook

Transamerica’s Facebook page soars over mainstream consumer-oriented brands with more than 550,000 likes and nearly as many page followers. Transamerica defines its voice by connecting the esoteric realm of finance with health and wellness, athletic events, and charitable outreach.


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For example, they publish an infographic highlighting how to find time to exercise while doing the usual daily activities, which was created in partnership with the American Heart Association. This is a unique approach to teaching financial service customers about other important considerations that relate to personal finance.

Their content is well distributed thanks to their social media team, who has mastered using compelling photography and infographics to drive their message home and capture attention on users’ news feeds.

2. John Hancock Financial’s Golden Tweets

John Hancock Financial uses Twitter almost exclusively to promote the Boston Marathon, an event it has become closely associated with after more than three decades of sponsorship. A roster of nearly 44,000 followers is testament to its ability to create relevant brand content before, during, and after races.

Their content marketing approach is especially impressive because their tweets subtly drive traffic to the main John Hancock Twitter, too. They’re using their sponsorship as an opportunity to deliver more value to their audience while driving engagement.

3. MasterCard Leads on Video Content

MasterCard has been building its video library on YouTube since 2006, and thanks to their consistent efforts over the long term, the quality shows.

Its channel is a rich cornucopia of different content campaigns. Many videos are fun brand awareness content that appeals to hip young consumers.

However, there’s also insightful thought leadership on next wave digital payment solutions. Travel is a major theme throughout its productions, which appeals to a specific subset of their target audience.

4. JPMorgan Chase Maps and Data Visualization

Now we get into the deep innovation. JP Morgan Chase shows off its fluency with data through its Maps and Data Visualization index.

Investors and others interested in all the inner workings of the nation’s financial picture can explore interactive maps with overlays that disclose everyday spending habits, major events in the financial market, gas prices, and much more.

5. Ideas with Morgan Stanley

Morgan Stanley Ideas is a collection of deep dive blog posts at the intersection of finance and futurism. Everything from e-commerce to the Chinese market to the looming economic effects of Gen Z is examined in delectable detail.

Short videos help set the stage for each post, but the lavish quality of the writing means Ideas stands out from a crowd of imitators. This is the ultimate content marketing achievement – creating content that is distinctly superior to your competitors’ content.

6. The Famous NerdWallet Blog

On the other side of the text content continuum is the NerdWallet blog. Look closely and you’ll see NerdWallet has a complete content team along with dedicated writers, and the difference is noticeable.

NerdWallet offers a sizzling and snappy look at key personal finance topics relevant to younger consumers. Small business and travel are anchor topics, giving the blog a lifestyle feel that is unique in the financial industry.

7. SoFi Online Calculator Center

Some of the top content marketing examples include tools to make your life easier. Tackling finance means crunching a lot of numbers, of course, so audiences in the finance world are likely seeking out educational resources that help them better understand certain circumstances they may be. 

Enter SoFi. They make things easier with a spiffy set of financial calculators that run the gamut of life’s finance topics. From student loans to mortgages to retirement, you can figure it all out – and each calculator page is conversion oriented, too.

8. Kabbage Stories

Don’t let the name throw you off. Kabbage Stories show you exactly how case studies can work in finance.

Striking a balance between detail and accessibility, these case studies are aimed straight at mid-market customers perfect for Kabbage business loans. Leads can see problems like theirs solved through Kabbage and then take the next step seamlessly.For lead generation and brand building, content counts. There are amazing stories your content can tell, no matter what industry you’re in. Use these eight outstanding content marketing examples for inspiration and you’ll find ways to capture your unique value in the financial world.

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Solve Real Problems

Technology should solve real problems. For example, CoreLogic has launched PanoramIQ, an intelligent property solution that delivers a more complete view of property data with more current and reliable sources than public-record data alone. Utilizing a combination of public and proprietary property datasets, a unique property ID, machine learning and advanced analytics, PanoramIQ provides lenders, mortgage industry professionals and government entities with deeper, more accurate and complete property insights, allowing clients to make better decisions in a timely and efficient manner. 


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Using a proprietary methodology, CoreLogic is able to efficiently bring thousands of disparate property data sets together through PanoramIQ. Traditional sources of property information, such as public-record data alone, can often have gaps or fail to reflect the latest information on a property. By bringing together a variety of property data sources, combined with advanced analytics, PanoramIQ delivers an up-to-date, comprehensive view of a property.


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“PanoramIQ brings a more complete and reliable source of property intelligence that fills gaps found in the traditional outdated systems. Based on an unmatched breadth of property information sources and sophisticated logic, CoreLogic is uniquely positioned to identify the most accurate sources of property data so clients have a more complete view of a property,” said Shaleen Khatod, executive, data and advisory solutions at CoreLogic. “As mortgage and refinance volumes continue to decrease, it’s important for those in the mortgage industry to have instant and reliable information on a property so they can identify high-quality leads and make timely and competitive underwriting decisions.”


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According to CoreLogic research, 27 percent of property records nationally have gaps within public-record data. Additionally, 18 percent of property records nationally have data attributes that CoreLogic identifies as more accurate than public record alone. Unlike sources such as tax assessor information, which are typically updated annually, PanoramIQ relies on a variety of proprietary information sources to provide more up-to-date reports. PanoramIQ uses artificial intelligence to scan multiple sources of data, link the data to a unique property ID, analyze and interpret changes and updates and uses advanced analytics to identify the most reliable information. This extensive process enables PanoramIQ to be a more complete, current and compliant view of property data. 


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“When information on a property isn’t reported accurately, it can have costly effects for those involved in the process. For those responsible for mortgage portfolios, an error in data reporting can lead to poor lending decisions or missed opportunities,” said Sherrie Clevenger, principal, product management at CoreLogic. “PanoramIQ is designed to turn data points into sales, change how property data is analyzed and improve decision making. It’s about changing the way property data is analyzed, so we can help lessen the amount of errors and build trust back into the system.”

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Success In The Era Of FinTech

Between robo-advisers, blockchain and biometric data to access bank accounts, a new era of accelerated technology transformation has emerged, affecting every aspect of financial services and altering the banking experience. 

As quickly as new technology surfaces, so too are long established banking tools, such as paper checks, being extinguished. We are experiencing remarkable growth in online payments in the U.S., which has been behind Europe and Asia in adoption up until now. Currently, three-fourths of the transactions processed through U.S. banks are digital. The industry has also been focused on real-time payments, as companies like Venmo and PayPal shift consumer expectations and cater to their need for immediacy. 


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These advancements in technology are driving the entire market to a more digital-centric environment, which could put earnings and capital at risk for many banks. In fact, McKinsey estimates legacy financial institutions could see profits decline between 20 and 60 percent by 2025 due to fintech disintermediation.


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Moreover, consumer expectations continue to evolve, especially as we witness the biggest transfer of wealth in history. With this new generation of consumers, financial institutions can expect new demands, particularly in mobile, internet and other fully digital appliances. Not surprisingly, these new consumers are looking to online provides such as VaroMoney, Venmo and Kabbage. They view traditional banks and lenders as outdated and unable to deliver the types of products and services with the convenience they expect. 


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In fact, a study by Fidelity National Information Services (FIS) found that only 23 percent of customers believe their financial institution is meeting their expectations. In response, some institutions are digitizing the lending experience, but many are still losing out to the online, alternative institutions due to convenience and speed in decisioning. 


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Mortgage lenders are also being impacted by this technological shift. Last year, Quicken Loans passed Wells Fargo as the largest mortgage lender in America. Nontraditional lenders like Zillow are adding even more pressure to traditional mortgage lenders to meet the demands of today’s consumer. In both examples, these organizations already have strong brand recognition, making it even more challenging for traditional institutions. The good news for mortgage lenders is that their execution doesn’t yet match their marketing, but that won’t last.

Finally, we’ve seen rapid growth in P2P and crowdfunding platforms like LendingTree and Monevo since the financial crisis. This makes sense. After the crisis, consumers lost trust in traditional financial institutions, and a supermarket to educate and facilitate choices is beneficial.  But just like in a supermarket, this shelf space is purchased, and consumers can be misled.

We now live in a digital world – we see this in the younger generations just coming of age to use financial tools. My 6-year-old sons mastery of all things digital is a great reminder of this every day. This technology is reshaping expectations, changing the financial services industry and fueling competition as new types of organizations emerge, all contending for market share. In response, traditional lenders must digitize the customer experience, leverage technology and data and prioritize security and safety.  

Create a Truly Digital Customer Experience

A digital customer experience is no longer a benefit. It’s a requirement for today’s lender. Millennials and the quickly emerging Gen Z market expect to do anything and everything from their smartphones, and it’s not just them. Older generations are also becoming more comfortable and reliant on digital channels. My 78-year-old mother is an ardent user of her iPhone for communications, healthcare, financial and travel information. Lenders must now deliver a seamless customer experience across all channels and devices. 

For many traditional lenders, there is a lack of consistency between channels. As mobile becomes a primary channel, lenders must embrace it and explore ways to leverage it to enhance the value they provide to consumers. 

Lenders must also evaluate their digital and in-branch experience and ensure consistency between the two as well. We are working hard on this at Gateway.  Leveraging the Internet of Things and wearable technologies will be key to success. By looking to innovators like Apple and Google, lenders can create unique services like scheduling appointments with loan officers from their Apple Watch or Google assistant. 

Additionally, immediacy and real-time payments are important. A digital platform should alert users of payment dates, enabling them to avoid late payments. The possibilities are endless, but creating a superior digital experience is critical for competing with today’s technology-driven alternative lenders.  

Leverage Modern Technology, Data and the Cloud 

Increasingly, alternative lenders beat out traditional lenders because of the speed of the application processes, fast decision-making and the convenience of an online platform. In response, lenders must leverage technology and data. With the right systems in place and adequate data, lenders can speed up decisioning and create a more convenient and simple process for borrowers. 

Cloud technology is also critical and enables lenders to implement real-time updates to loan origination software that leverages data for a faster decisioning process. For any lender not currently operating on cloud-based technology, this year is the time to begin migrating. 

In the Wake of Data Breaches and Cyberattacks, Security Must Be a Priority 

Finally, security must be a priority, especially as a digital environment exposes financial institutions and lenders to greater risks and security concerns. In fact, in 2018 alone, data breaches compromised the personal information of millions of people around the world. T-Mobile, Quora, Google and Orbitz were among some of the companies that faced costly breaches, and Facebook dealt with several that affected over 100 million users. 

Between the growing number of data breaches and cyberattacks, digital mortgages are substantially at a higher risk than standard ones. Lenders can no longer afford to rely on old infrastructure. Instead, they must focus on upgrading their digital experience and prepare for the possibility of targeted attacks, which is inevitable. 

Ultimately, by increasing their emphasis on security protocols and educating their employees and customers, traditional lenders can secure their digital assets.As technology evolves more quickly, traditional lenders must prioritize the customer experience and place the needs and expectations of the borrower first. If not, they will continue to lose out to alternative lenders, who are rapidly gaining market share. 

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