The LIBOR Transition

September, 24, 2019 – by Kyle Kaminski

The London Interbank Offered Rate (LIBOR) is a benchmark interest rate that historically represented an average estimate of interest rates that the major global banks lent to one another on a short-term basis. Although originated in 1969 and currently one of the most frequently used interest rate benchmarks in lending, formal data collection did not occur until the mid 1980’s. It is estimated that approximately $250 trillion in LIBOR-benchmarked product is outstanding.

In 2012, financial regulators (currently the Financial Conduct Authority (FCA)) began requiring that reporting for LIBOR be based on actual transactions rather than estimates. Because of the new reporting requirement, several banks removed themselves from the process, resulting in declining participation. Additionally, the reporting requirement came at a time when unsecured borrowing was declining as banks began favoring overnight secured borrowing instead. With the decline in participation and in the reliability of the data being provided, experts began to question the validity of LIBOR as a benchmark. In fact, because of a growing sense of unreliability from market participants, the FCA decided that starting at the end of 2021 they would no longer require participating banks to continue to report nor would they publish the rate publicly, thus effectively ending LIBOR as a viable reference rate beyond 2021.

Following this announcement, consensus among lenders was that the lack of published rate could be problematic. Market participants are now contingency planning should LIBOR cease to exist. Appropriate plans should include the following: (i) a full review of loan portfolio to determine potential risk exposure (loans that mature after 2021), (ii) review of loan documentation, particularly interest-rate fall back language to determine potential risk exposure (unclear or inconsistent language, silent on fallback, etc.), (iii) after review, modify or sell loans that may have deficient fall back language, (iv) implement/review protocols to ensure they will be followed correctly, including the proper servicing of loans should fallback language be required to go into effect, (v) review preparedness of servicing systems to correctly capture modifications to affected loans in the event of a transition and (vi) consider originating new product using an alternative risk free rate.

When modifying existing loans or originate new ones, lenders should transition to alternative risk-free rates such as the Secured Overnight Financing Rate (SOFR), which is currently backed by the Alternative Reference Rate Committee (ARRC). SOFR, which was established in April 2018 and currently monitored by the Federal Reserve Bank of New York, is one of the most popular alternative rates. The biggest difference between SOFR and LIBOR is that SOFR is entirely based on actual secured transactions that have occurred. Because of this, it has predominantly been a slightly lower rate than LIBOR over their corresponding lifetimes as displayed in the table below:

 

While it’s impossible to predict where LIBOR rates will be relative to any alternative rates when a potential hard stoppage of the publication of LIBOR occurs, at various times LIBOR and SOFR have been the same, or SOFR has been higher than LIBOR. This uncertainty may make modifications with borrowers a challenging proposition. Therefore, as stated above, lenders should assess the viability of selling off loans with deficient fall back language (or loans to borrowers that may be unresponsive) to mitigate portfolio risk in advance of a transition. Strong secondary market pricing from financial institutions that are equipped to navigate deficient rate language may result in a less costly outcome than internal resolution.

December 14, 2018

In this Q&A, Michael Britvan, Managing Director Loan Sale and Asset Sale group at Mission Capital and Allison Israel, Product Manager of Mission Capital give insights into how machine learning and artificial intelligence will have a broad impact on lending operations.

How do you see artificial intelligence and machine learning impacting the mortgage space?

Israel: There are various applications for artificial intelligence across the mortgage industry, but one area where we’re already seeing machine learning make an impact is the analysis of loan portfolios.

When banks explore the sale of loan portfolios in the secondary market, they produce data tapes containing relevant loan, collateral, and borrower information from their servicing systems. Field names in these tapes frequently vary by servicing platform as there is currently limited industry standardization. For example, a data field in one loan tape might refer to “Origination Date,” while another shows “OrigDate” and a third is “Loan Origination Date.” Although each of these fields refers to the same thing, the fact that they are labeled differently means that an analyst looking to load a model might spend considerable time deciphering column headers and normalizing data.

Machine learning has the power to take this manual process and perform it automatically. For example, it is able to recognize that “OrigDate” means “Origination Date.” Additionally, when the system is processing a new tape and finds a term it doesn’t recognize, it uses natural language processing to parse the word and find the closest match. The more tapes we put through the system, the smarter it gets. A few months ago–when we first deployed the system internally–it generally recognized around 40 percent of the fields. But, as it learns more, and processes a greater number of tapes, we expect that number to climb closer to 90 percent.

Would you say that the greatest benefit of machine learning is time savings?

Israel: While time savings is an important factor, having standardized field names from the machine learning model also allows us to apply a standard set of “rules” within the same software. For example, with all tapes using the term “Origination Date,” we can tell the system that “Origination Date” must come before “Maturity Date,” and it will flag any loans that don’t comply with the rule. We currently have about 250 rules, and they are instrumental in enabling us to improve data integrity by catching data issues programmatically.

Conventionally, analysts have spent up to 80 percent of their time in Excel normalizing data, validating information in the tapes, and resolving errors. This results in very little time to analyze the value and potential of the portfolios at hand. With newly developed software, we’re leveraging machine learning to flip the scale and enable analysts to spend less time manually manipulating data tapes and more time on the actual analysis.
Across the industry, loan analysis and trading are made infinitely more efficient by introducing machine learning models and enhancing those models with historical big data. The key to leveraging big data is the ability to normalize it first.

What are the other benefits mortgage professionals realize from this technology?

Britvan: The technology empowers all mortgage professionals to validate, analyze, and visualize data more efficiently. Depending on the user and firm, this can translate into a range of different benefits.

Banks leveraging this technology might be able to gain better insight into their portfolios. By cleaning up data and eliminating errors, they are also better able to manage their service providers. For example, with a better handle on their portfolio, it will become easier for banks to spot-check loan servicers to ensure accurate reporting and potentially even audit remittances.

Investors acquiring whole loans are able to spend more time on analysis and less time cracking tapes and stratifying portfolios.

Do you think these innovations will have a broader impact on the whole loan sale market?

Britvan: Over the past decade or so, there’s been a significant shift in the perception of trading whole loans on the secondary market.

Ten or twelve years ago, selling loans on the secondary market was often an indicator that the seller had a problem on their hands, and the decision to sell stemmed from a desire to remove the problem from their books. That perception has changed. Today, the speed of transactions has increased, while the number of participants in the secondary market for whole loans has climbed significantly. Whole loans are a relatively liquid asset, and many banks routinely tap the secondary market to manage their loan portfolio.

We expect technology to increase efficiency in analyzing loan portfolios which should, in turn, expand the universe of buyers in the secondary market. Right now, most buyers considering entering the market rely on an analyst to clean and validate data prior to loading a model. With the strides we’re making in producing tools that clean up the data automatically, it allows investors to focus on finding value rather than allocating resources to data manipulation.

Do you think there are other notable tech trends that will have a significant effect on the secondary loan sale market?

Britvan: One area that has a lot of untapped potential is the incorporation of big data into mortgage analysis. When analyzing a loan portfolio, the quality of the valuation we can produce is often limited by the quality of data we receive. Key data points that are stale or absent require that assumptions be made.

By taking a big data approach to updating stale data or making assumptions, we can improve our estimates. For example, if we’re analyzing a multifamily property, we could leverage things like demographic trends, market occupancy, existing and future inventory, and housing data to make assumptions regarding a property’s current and projected future occupancy. This means that we are no longer just filling in missing or stale data but are also using historical trends to predict the market. This introduces brand-new inputs into our models that would have previously been unavailable without the breadth of data at our fingertips today.

Big data analysis of external factors, combined with proprietary market knowledge gleaned from our whole loan trading activity, will provide a better basis for secondary market participants to analyze loan tapes. We expect the industry to make significant strides in incorporating third-party data into their analysis in the years ahead.

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From, ‘Silicon Nation: Tech Firms, Chasing Millennial Workers, Look Beyond the West Coast’ published November 6th, 2018 in the Commercial Observer

Ari Hirt, Managing Director of The Debt & Equity Finance Group, shares his insight on the national expansion of tech firms, and the impact those moves have on a neighborhood in today’s Commercial Observer.
[Click here to continue reading the full article now]

[Published November 6, 2018 in the Commercial Observer]
When tech firms come to the neighborhood, they can have transformative effects far beyond the office space they lease. That, at least, is the perspective of Ari Hirt, a managing director who works on both debt and equity deals at Mission Capital.

“What Google did to Chelsea [in Manhattan] made that neighborhood much hotter than it was. The same phenomenon has occurred in the West Loop of Chicago,” Hirt said. Given that companies like Google and Pinterest have hung out their shingles there, “now, everyone wants to be in the West Loop,” he said.

Peter Thiel, the Silicon Valley mainstay who founded PayPal, Clarium Capital and big-data contractor Palantir Technologies, has never shied away from iconoclastic gestures.

In 2016, Thiel bucked his fellow new-economy titans and offered an unqualified endorsement to Donald Trump; he promoted efforts to forge floating societies in international waters; he’s even advocated space colonization.

But one of the entrepreneur’s boldest heresies came earlier this year, when he launched a broadside at Silicon Valley itself. In February, Thiel announced that he would uproot his technology ventures from their Silicon Valley haunts for Los Angeles, arguing that the birthplace of the software industry had become too insular. …

[Click here to continue reading the full article now]

YouTube video

Mission Capital’s Jordan Ray discusses our joint venture with UK-based firm, Brotherton. Jordan is a principal on the Debt & Equity Finance desk at Mission Capital.

Jordan Ray is the Principal of The Debt & Equity Finance Group at Mission, which he founded in 2009. Jordan has been honored with such industry awards as the 2016 Real Estate Finance and Investment Magazine – Mortgage Broker of the Year Award, the 2013 and 2012 Observer Top 20 under 35 and the 2017 NYU Schack Institute Financing Deal of the Year. Jordan sits on the board and co founded EquityMultiple – an online marketplace real estate finance company – in 2015. Jordan is also actively involved in UK/European real estate financing.

ABOUT BROTHERTON:
Mission Brotherton is an alliance between Mission Capital and Brotherton Real Estate. Combining Mission’s institutional reach with Brotherton’s deep knowledge of the UK and European markets, allows us to provide real estate capital solutions to our clients, globally.

Mission Brotherton

ABOUT JORDAN RAY:

Team

LEARN ABOUT THE DEBT & EQUITY FINANCE DESK HERE:

Debt Equity

VISIT MISSION CAPITAL’S WEBSITE:

Home

Mission Capital’s Jordan Ray discusses recruiting. Jordan is a principal on the Debt & Equity Finance desk at Mission Capital.

ABOUT JORDAN RAY
Jordan Ray is the Principal of The Debt & Equity Finance Group at Mission, which he founded in 2009. Jordan has been honored with such industry awards as the 2016 Real Estate Finance and Investment Magazine – Mortgage Broker of the Year Award, the 2013 and 2012 Observer Top 20 under 35 and the 2017 NYU Schack Institute Financing Deal of the Year. Jordan sits on the board and co founded EquityMultiple – an online marketplace real estate finance company – in 2015. Jordan is also actively involved in UK/European real estate financing.

LEARN MORE ABOUT JORDAN RAY:
www.missioncap.com/team/?member=jray

LEARN ABOUT THE DEBT & EQUITY FINANCE DESK HERE:
www.missioncap.com/debt-equity/

VISIT MISSION CAPITAL’S WEBSITE:
www.missioncap.com

YouTube video

Mission Capital’s Jordan Ray discusses Construction financing. Jordan is a principal on the Debt & Equity Finance desk at Mission Capital.

ABOUT JORDAN RAY
Jordan Ray is the Principal of The Debt & Equity Finance Group at Mission, which he founded in 2009. Jordan has been honored with such industry awards as the 2016 Real Estate Finance and Investment Magazine – Mortgage Broker of the Year Award, the 2013 and 2012 Observer Top 20 under 35 and the 2017 NYU Schack Institute Financing Deal of the Year. Jordan sits on the board and co founded EquityMultiple – an online marketplace real estate finance company – in 2015. Jordan is also actively involved in UK/European real estate financing.

LEARN MORE ABOUT JORDAN RAY:
www.missioncap.com/team/?member=jray

LEARN ABOUT THE DEBT & EQUITY FINANCE DESK HERE:
www.missioncap.com/debt-equity/

VISIT MISSION CAPITAL’S WEBSITE:
www.missioncap.com

Jordan Ray, Principal of the Debt & Equity desk, is a major proponent of FinTech that modernizes the ‘old economy’ business of real estate. Always ahead of curve and owner of an impressive CRM, you don’t want to miss Jordan’s insight.

Watch the first two parts of this video series here:
https://www.missioncap.com/news/jordan-ray-principal-on-mission-capital/

ABOUT JORDAN RAY
Jordan Ray is the Principal of The Debt & Equity Finance Group at Mission, which he founded in 2009. Jordan has been honored with such industry awards as the 2016 Real Estate Finance and Investment Magazine – Mortgage Broker of the Year Award, the 2013 and 2012 Observer Top 20 under 35 and the 2017 NYU Schack Institute Financing Deal of the Year. Jordan sits on the board and co founded EquityMultiple – an online marketplace real estate finance company – in 2015. Jordan is also actively involved in UK/European real estate financing.

LEARN MORE ABOUT JORDAN RAY:
www.missioncap.com/team/?member=jray

LEARN ABOUT THE DEBT & EQUITY FINANCE DESK HERE:
www.missioncap.com/debt-equity/

VISIT MISSION CAPITAL’S WEBSITE:
www.missioncap.com