Category Archives: Servicing

Built Technologies hires new chief technology officer

Built Technologies, a technology company bringing construction lending to the digital age, recently appointed Matthew Russell as its new chief technology officer.

This new hire marks the beginning of the company’s plans for expansion. Russell joins Built on the heels of a significant $21 million series A capital raise with Index Ventures and Nyca Partners in November, which allowed the tech innovator to deepen its team, accelerate its growth and bolster investments in data utilization.

“Built is solving a significant problem in construction lending, and I’m excited to be leading an incredibly talented technology team that is delivering a definitive solution for managing loans that is quickly becoming the de-facto standard for financial institutions across the country,” Russell said. “Our platform already allows our customers to make smarter, faster, better decisions, and our recent investment from Index Ventures allows us to accelerate our development efforts to serve an even broader segment of the market in 2018.”

Russell brings more than a decade of experience to Built, where he will be responsible for overseeing the strategic development of technical operations of its collaborative construction lending platform. Previously, At Digital Reasoning, he led the corporation’s technology, data science, and intellectual property strategy. Russell also previously served as an active duty U.S. Air Force officer, deploying overseas as a defense intelligence contractor, facilitating the enforcement of financial compliance, improving cancer treatment with advanced software, and consulting with businesses on data and data science strategy.

“Matthew is an integral addition to our team as we enter an era of unprecedented growth for Built,” Built CEO and co-founder Chase Gilbert said. “With his impressive background in technology enterprise and experience in executive leadership, we’re confident Matthew will not only elevate Built and our product, but his expertise, especially in data analysis and utilization, will transform the entire industry.”

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Fannie and Freddie regain capital reserves; withhold billions from Treasury

It’s official.

Fannie Mae and Freddie Mac have capital reserves again.

As expected, the government-sponsored enterprises on Friday made their quarterly dividend payments to the Department of the Treasury.

But, thanks to the new agreement between the Federal Housing Finance Agency and the Treasury, each of the GSEs withheld billions from the Treasury to ensure that each has enough capital on hand to “cover other fluctuations in income in the normal course of each Enterprise’s business.”

Under the previous version of the Preferred Stock Purchase Agreements that went into effect when the government took the GSEs into conservatorship, Fannie and Freddie send dividends to the Treasury each quarter that they are profitable.

The PSPAs also stipulated that the GSEs were prohibited from rebuilding capital and each of the GSEs’ capital base was required to be reduced, with their capital reserves scheduled to be drawn down to $0 in 2018.

But that all changed earlier this month when the FHFA announced a new agreement with the Treasury that allows the GSEs to hold a $3 billion capital reserve.

Collectively, the GSEs made dividend payments this week to the Treasury of $2.897 billion. Of that, $2.249 billion came from Freddie Mac and $648 million came from Fannie Mae.

But those amounts are far less than the amount of profit that each GSE made in the third quarter.

Freddie Mac’s profit was $4.7 billion, while Fannie Mae’s checked in at $3 billion, but unlike previous quarters, the GSEs did not send all of their profits to the Treasury.

Based on some rough calculations, Freddie withheld $2.451 billion from the Treasury, while Fannie withheld $2.352 billion.

As the chart from the FHFA states:

As set forth in the Letter Agreement dated December 21, 2017, amending the Certificate of Designation of Terms of Variable Liquidation Preference Senior Preferred Stock, Series 2008-2, the dividend amount is the Net Worth Amount for the dividend period minus the Applicable Capital Reserve Amount. Beginning in 2018, the Capital Reserve Amount is set at $3 billion under most circumstances.

With the $2.897 billion sent to the Treasury for the third quarter, Fannie and Freddie have now paid approximately $278.783 billion to the Treasury in dividend payments since the fourth quarter of 2008.

(h/t Bloomberg’s Joe Light)

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Beyond the digital POS: Time to focus on the underwriter

If 2016 was the year of compliance, then 2017 will go down as the year of the customer experience. At recent conferences, FinTech startups and mega lenders have been actively presenting new front-end point of sale solution demos designed to take the pain points and hassles out of applying for a mortgage. These efforts have energized our industry around the concept of a digital mortgage and told consumers that getting a mortgage is simple, fast and easy, even though that’s not always the case.

Lost in all of the excitement, however, is the disconnect between the digital consumer experience and the cobbled together, often manual processes, that make up the back-end of the mortgage process. Yes, many LOS, POS and fintech providers claim to have already addressed this, but solving for borrower experience and delivering a digital data stream are only part of a much larger issue. For many lenders and their loan officers and underwriters, the process is still characterized by inefficiency, inaccuracy and lack of standardization. Sure, we know some of the largest market players have significantly invested in their backend processes to improve their efficiencies and time to close, but most other lenders don’t have the resources to make these kinds of investments.   

So, how can everyone else gain efficiency in their underwriting processes so they can remain competitive?

Companies are actively working on digital solutions that will help improve the underwriter’s productivity and experience. The underwriter is plagued with inefficient, time-consuming tasks forcing them to import and manually enter data into spreadsheets. A quick glimpse of the average underwriter’s desk shows the presence of “time thieves” in the stacks of files, the dueling computer screens, and the ad-hoc calculations that will eventually find their way back into the final loan file. And, in many cases, these calculations are submitted without any explanation of how they were determined. This lack of a repeatable, standardized, documented and automated process is inefficient, can lead to errors and perpetuates the need for redundant reviews and due diligence.

One of the obstacles that comes with underwriting a mortgage is the income verification and calculation process, which often delays the decision. We hear most lenders say that they continue to perform a majority of this process manually. The inefficiencies with this traditional method are obvious and, by some estimates, result in up to 10 to 15 hours spent processing a loan including six to seven review sessions with the processor and underwriting teams.

If a lender were building an ideal platform for disrupting the current underwriting process and workflow, it would have to be:

Efficient: It would avoid needless busy work such as manually entering data into checklists and tabulating calculations in Excel.

Digital: Information, such as tax returns, pay stubs, W-2 and bank statements, should be either submitted digitally or through paper forms that can be digitized.  Whatever the format, standardizing a data model and providing the capabilities to transform the myriad of documents and data sets into a digital structure will unlock the ability to automate, standardize, and measure all the processes that make underwriting such a difficult task today.

Configurable: While calculations are based on GSE guidelines, lenders should also be able to layer in their own criteria so the analysis can fit their specific underwriting criteria. For example, while active income streams, salaries, wages, commissions and bonuses, are pretty straightforward, passive income streams, such as owned businesses, royalties, rental and multi-level marketing, and portfolio income, such as stocks, shares, capital gain, collectibles and currency exchange, must be able to be addressed in a similar fashion with full transparency. As many underwriters like to say, there are no standard loan files: “Every borrower is unique.”

Consistent and Accurate: In today’s world, if you gave the same loan file to ten underwriters it’s conceivable, even likely, that ten different income amounts would be calculated. By standardizing the workflow with a consistent and automated process, lenders, and their investors, will gain greater confidence in the quality of their loans and feel empowered to start driving costs out of the origination and underwriting processes.

Compliant: As the use cases for automation and aggregation continue to expand in the mortgage industry, regulation is sure to follow. Any income and asset verification and analysis solution must provide comprehensive and clear audit trails, with levels of detail that will trace source data and the analysis of it from inception to the underwriting decision. Regulatory agencies such as the CFPB are demanding more transparency for oversight to provide consumers with more control.

While a transformation of the lending process has certainly begun, many of the “big innovations” don’t deliver a truly digital mortgage outcome. Very few borrowers fall into income profiles that can be validated with a single data source and any time there’s an exception, the process reverts to the same old workflow everyone knows and does not love today.

So, what would an ideal solution look like? First and foremost, it needs to work for all borrowers and all loans. Whether a borrower consents to providing digital data and bank credentials or elects to only provide printed copies of every document requested, the solution needs to be able to handle it. Data transformation, digital data supply chains, and the automation of the underwriting feedback loop must be woven into a platform that enables a more simple and intuitive process and experience. The result should be that only the relevant data is actually pulled into the process. Standardizing the analysis, reducing overhead in the form of inefficient manual calculations and providing a UI and functionality that enables transparency and tracking of the entire process should be integrated into in a real solution.

We believe that as an industry, we now have unprecedented access to the data, technology and knowhow to start this transformative process to support and enhance the critical role that underwriters play. We look forward to being a key contributor in this evolution.

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