October Bellywrap.indd 1 10/1/2019 2:02:34 PM...staff issued a no-action letter to Upstart in 2017. In addition to market signaling, one primary goal of the letter was to afford the

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November/December 2019 Asset Securitization Report 3asreport.com

Bots ascendingIn February, a startup company with dual headquarters in Israel and New York launched what is believed to the first “A.I.” securitization – a transaction of unsecured consumer loans that was fully structured, collateralized and sold to a private investor using only the firm’s proprietary artificial-intelligence platform.

Pagaya Investment’s inaugural deal was unique in two ways. The deal was collateralized by Pagaya’s loan-selection tools that bid on individual

loan assets, rather than taking on pre-selected pools of loans from a marketplace lender. The platform uses algorithms covering more than 1,600 attributes to provide unique insight into projected risks and returns on each unique loan.

Secondly, the assets will also be managed through the platform’s machine-learning analysis, with buy/sell/hold decisions on the actively managed portfolio determined by algorithms rather than the judgment of a living, breathing asset manager.

Pagaya’s technology has been used to build and market three subsequent deals this year. This month, ASR looks at how Pagaya and other firms are raising A.I’s influence in financial services and asset management strategies. - Glen Fest

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4 Asset Securitization Report November/December 2019

ABS: Packaged by AI, Managed by AIBanks and lenders have made inroads in analytics and automa-tion with machine-learning tech-nology. Will asset management follow suit?

06

Observation05 Doing better by MPLsThe CFPB should offer some form of guid-ance to spur innovation, a former official with the bureau says.

CLO14 Tetragon’s debt playThe asset management firm will comple-ment its CLO equity strategy by also adding exposure to the debt side of loan portfolio deals.

16 Lacking ‘J.Crew blockers’Despite concerns over tactics that unilater-ally remove assets from loan packages, few lenders have sought to block such moves.

18 Golub’s SaaSy debutThe middle-market lender markets its first securitization backed by ‘late-stage’ loans to VC-funded “software-as-a-service” firms.

ABS19 Flexing fintech regsThwarted so far at the federal level, financial tech companies are hoping states will work jointly toward regulatory standards.

20 Speedbump in subprimeSantander Consumer sees an uptick in subprime auto loans, with more than usual defaulting within months.

MBS22 JPMorgan’s CRT playThe notes in JPMorgan’s new credit-risk transfer deal are structured to reference a pool of 979 mortgage loans that will remain on the bank’s own books.

23 GSEs: Bring it onHousing finance reform could bring new entrants to the secondary market. Fannie and Freddie execs say they welcome the possibility.

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Asset Securitization Report - (ISSN # 1547-3422) Vol. 19, No. 8, is published 8 times a year by SourceMedia, One State Street Plaza, 27th Floor, New York, NY 10004. Postmaster: Send address changes to Asset Securitization Report, SourceMedia, One State Street Plaza, New York, NY 10004. For subscriptions, renewals, address changes and delivery service issues contact our Customer Service department at (212) 803-8500 or email: [email protected]. All rights reserved. Photocopy permission is available solely through SourceMedia, One State Street Plaza, 27th Floor, New York, NY 10004. For more information about Licensing and Reuse of Content: Contact our official partner, Wrights Media, about available usages, license and reprint fees, and award seal artwork at [email protected] or (877) 652-5295 for more information. Please note that Wright’s Media is the only authorized company that we’ve partnered with for SourceMedia materials. No data herein is or should be construed to be a recommendation for the purchase, retention or sale of securities, or to provide investment advice of the companies mentioned or advertised. SourceMedia, its subsidiaries and its employees may, from time to time, purchase, own, or sell securities or other investment products of the companies discussed or advertised in this publication.

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004_ASR1119 4 11/19/2019 8:59:14 AM


ABS: Packaged by AI, Managed by AIBanks and lenders have made inroads in analytics and automa-tion with machine-learning tech-nology. Will asset management follow suit?

MBS22 JPMorgan’s CRT playThe notes in JPMorgan’s new credit-risk transfer deal are structured to reference a pool of 979 mortgage loans that will remain on the bank’s own books.

23 GSEs: Bring it onHousing finance reform could bring new entrants to the secondary market. Fannie and Freddie execs say they welcome the possibility.

The Consumer Financial Protection Bureau recently finalized three policy tools meant to promote financial innovation by offering some regulatory certainty. But the agency may need to go further to convince fintechs such tools are safe and beneficial.

Two of those tools — the no-action letter and the compliance assistance sandbox — equip the CFPB with broad authorities to address various regulatory questions, includ-ing fair-lending risk associated with the use of machine learning and alternative data in credit underwriting.

One example of this is in an August blog post that updated its first issued no-action let-ter to Upstart Network, an online marketplace lender that uses alternative data for under-writing. In the post, the CFPB encouraged fintech lenders to take advantage of such policy tools to reduce their own fair-lending compliance risk.

More of these no-action letters that offer a “safe harbor” from the CFPB might benefit a handful firms, but the market as a whole will not reap the rewards until the agency issues generally applicable guidance.

When Upstart applied for the no-action letter in 2017, there was a tremendous amount of regulatory uncertainty around disparate impact testing — when disparities are found between groups, though unintentional — as related to the use of machine learning and nontraditional data.

Regulatory agencies had little experience with those new and innovative credit models. And there was little regulatory guidance to help new fintech lenders monitor and man-age the enhanced fair-lending risk inherent in those models.

It was against that backdrop that CFPB

staff issued a no-action letter to Upstart in 2017. In addition to market signaling, one primary goal of the letter was to afford the CFPB a ringside seat to gain experience and expertise that would enable the agency to for-mulate a sound, general policy in the future.

The Upstart letter has a number of novel ideas.

For example, a (very welcome) regulatory innovation is the use of a hypothetical model that contains traditional application and cred-it variables, but does not use machine learning as the baseline for credit-access analysis and disparate impact testing.

Too often, regulators compare the out-comes of innovation to a distant ideal rather than an imperfect status quo. Regulatory real-ism that recognizes the value of incremental improvements and gradual harm reduction is a step in the right direction.

The Upstart no-action letter for the first time provides a detailed roadmap of fair-lending compliance. Unfortunately, all of the regulatory and compliance innovation in the letter is confidential and so far, benefits just one company.

The regulatory uncertainty that existed in 2017 remains unchanged. What has changed, however, is that the CFPB (through the Upstart collaboration) has now developed a wealth of knowledge about how to manage and mitigate fair-lending risk for machine learning models.

Now is the time to leverage those insights to develop policies that benefit not just Up-start but the entire industry.

A good start would be for the CFPB to dis-close key aspects of model risk management and compliance from its first no-action letter.

How should a hypothetical model be con-

structed? How can companies use such a model in access to credit evaluation and disparate impact testing? What are the steps firms may take to monitor and manage disparate impact risk?

While there may be many paths to compliance, answers to those questions will provide specificity so firms can learn and develop their own compliance approaches. Sharing the lessons from the Upstart no-action letter essentially provides an example of a safe harbor for fair-lending compliance that can address much of the existing regulatory uncertainty.

It is also important for the CFPB to work with the pruden-tial banking agencies to issue formal fair-lending compliance guidance, since bank regulators enforce the Equal Credit Oppor-tunity Act.

This would benefit not only fintechs but incumbent banks that also wish to safely use machine learning and alterna-tive data in their credit deci-sions. Such joint guidance would provide ultimate certainty to the entire marketplace.

While the Upstart no-action letter was an example of policy innovation, issuing more of such letters on the same ground would be equivalent to innovation-by-permission. Let the market do what it does best: innovation through competition. ASR

Dan Quan is an adjunct scholar at the Cato Institute’s Center for Monetary and Financial Alternatives. He was previously was a senior ad-viser to the director of the CFPB and head of the bureau’s Project Catalyst

Observation

CFPB can do better by MPLs

By Dan Quan

The bureau should offer some form of guidance to spur innovation, a former official with the bureau says

005_ASR1119 5 11/19/2019 8:59:15 AM


By Glen Fest

Gal Krubiner is clicking through a PowerPoint presentation on his laptop, pausing on a picture of a 1980s era New York Stock Exchange floor.

“Recognize that?” he asked.“You have 5,500 people working there. You had people trading from

the stomach. The back office was full of papers – everything was different,” said Krubiner (who, it should be noted, at 31 years old came of age well after the photo was taken.) “Ninety percent of those people became irrelevant.”

Krubiner, the chief executive of New York-based Pagaya Investments, is not giving a history lesson. He’s pitching the idea that technology firms are poised to do something similar in asset-backed securities and institutional asset management.

Earlier this year, Pagaya, a startup led by three Israeli-born principals, with tony offices in both New York and Tel Aviv, launched what it said was the securitization’s industry first robo-deal – a fully automated transaction in which collateral was compiled, priced and sold without

Packaged by AI, managed by AI

Banks and lenders have made inroads in analytics and automation with machine-learning technology. Will asset management follow suit?

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Packaged by AI, managed by AI

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any assist from human intervention.In the privately placed, $100 million

deal, Pagaya’s artificial intelligence platform pooled together individual, unsecured consumer loans directly from the managed portfolio of (at that time) an undisclosed lender. Typically, buyers of marketplace loans usually bid on static, preselected folders of loan collateral com-piled by the issuer.

The portfolio compilation criteria on the deal – and three subsequent issu-ances that have involved loans acquired from Prosper and LendingClub – were based on criteria encoded into the firm’s proprietary A.I. platform. The benchmarks for choosing the loans involve more than 1,600 attributes that Pagaya assigned from across any number of data points: borrower credentials, loan market and investor trends, macroeconomic factors, etc.

That same technology is also being used to actively manage the portfolio going forward with a short-duration, high-yield strategy of buying and selling loan assets determined by the cold logic from data accumulated by Pagaya’s machine-learning tools.

“The concept is very simple,” said Krubiner. Pagaya is “taking the three layers of asset management – deploy-ment, performance and operations – and asking the question if we need, and we do, to be an asset manager from scratch in data-driven asset classes, how does it look like?”

Rise of the botsMachine-learning inroads into financial

services has been well documented in recent years.

BNY Mellon has launched A.I.-based “bots” to automate many of bank’s functions that were previously manual tasks from employees (such as clearing U.S. Treasuries).

Banks like BMO Financial Group and Nordic bank Nordea are using A.I. to

function as online chat advisors to consumers.

A.I. is also being deployed by lenders and institutions for credit-decisioning, consumer behavioral analysis, fraud detection and internal operations. New York-based AlphaSense has developed an A.I.-based search engine used by banks and investment firms to analyze public corporate filings, research and news stories through natural language process-ing to ferret out trends in financial markets.

In addition, A.I. is being tapped for eco-nomic analysis and market predictions. Cambridge, Mass.-based Kensho Tech-nologies, for example, is a hedge-fund markets analyst software firm that got attention for projecting an extended drop in British currency following the 2016 Brexit vote in the UK, according to Fortune magazine.

(Kensho was acquired by S&P Global in 2018 for $550 million).

These first steps for big data analytics into financial services makes A.I. in portfolio and credit management a natural next step, said Brad Bailey, a research director in capital markets for fintech research firm Celent.

“When you look at fixed income broadly and credit broadly, it’s how people manage – not just down to the details of that construction, but how are you going to manage your hedges, your pricing and your, the different things that happen within the tranches,” said Bailey. “This can all be done in much more effective ways then it’s done.”

A.I. can help ABS investors in several ways. The tools can make greater use of reams of available data – such as faster comparisons and risk/return projections from Reg AB-II and disclosure data in

asset classes like auto loans and mort-gages – but can also gather and crunch more opaque information such as individual consumer behavioral data that might not be apparent in loan apps and credit bureau files.

“The big managers, they’re all going to be thinking about this as part of their portfolio,” including both in tactical strategies (i.e., trading and reinvestment) and improving efficiencies and transpar-ency to investors, said Bailey.

Under the hoodIn Pagaya’s case, the loans it acquires

and securitizes through its platform – Pagaya AI Debt Selection Trust – are chosen and bid on based on algorithms that measure an array of data beyond borrower FICOs, payment history and job title.

Pagaya will apply macroeconomic data, for instance, to individual loans that may uncover hidden risks.

Krubiner points to examples such as an unsecured loans to a construction worker and a nurse. While both may have similar credit scores and income, the construction worker is in a field with four times the historical employment volatility of the healthcare worker.

So instead of taking on both loans with similar attributes with similar bids, Pagaya might avoid the higher-risk loan or seek a premium for it.

Pagaya may also consider paying a higher rate on a loan that is safer than its surface details reveal, if the algorithms determine the rate is right.

“The very basic type of [lending] models will ask the question, what is the [debt-to-income]. What is the monthly income and therefore what is the interest rate?” said Krubiner. “But when we are an asset manager, we care more than everything [about] performance. Not to lose money. We want to be in a situation where if the crisis comes, we are better off with our portfolio.”

“The concept to understand is there is no ‘good’ or ‘bad’ loan,” says Krubiner. “There is a loan that is priced well or not.”

PAG

AYA

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Pagaya’s technology, using API connections with its MPL partners, will continue monitoring each loan it purchas-es for institutional clients like Citigroup – scoring the underlying borrower’s updated credit profile, the lender’s underwriting model and managed portfolio performance, among other factors.

The goal is to formulate projected returns for Pagaya’s clients based on the thousands of data points that might uncover attributes that mitigate or enhance the decisioning factor.

This will factor in the ongoing manage-ment of the asset within the portfolio that promises a greater level of operational savings and less “from-the-gut” thinking on buying and selling.

“The concept to understand is there is

no ‘good’ or ‘bad’ loan,” said Krubiner. “There is a loan that is priced well or not.”

Alternative dataDan Petrozzo, a veteran technology

venture capitalist, likens the A.I. evolution to an ironic return to classic investing and lending: making more intrinsic decisions based on data that bankers and issuers may only otherwise glean from deep, one-on-one interaction.

“It’s very interesting. What the technology ultimately does, it’s making a personalized decision based upon a whole bunch of data,” said Petrozzo, who

once served as global head of technology for investment management at Goldman Sachs, and now leads fintech investments for venture capital firm Oak HC/FT (a key investor in Pagaya).

”This is what would have happened before FICO existed. [Bankers] would call you up. They would call your friends, do you work a steady job. They would look you in the eye, are you a good person.

“Effectively, that’s what the [A.I.] algorithm is doing at scale.”

The core, fundamental skillset for lenders, investors and fixed-income managers is derived from a simple concept.

What is a good investment – and what is a bad bet?

For decades, firms have increasingly poured millions into their intelligence-

“What the technology ultimately does, it’s making a personalized decision...that’s what the algorithm is doing at scale.”

Pagaya Investments chief executive officer Gal Krubiner

PAG

AYA

009_ASR1119 9 11/19/2019 8:59:27 AM


gathering mission to gain an edge to raise the odds of finding the former and avoiding the latter.

But in the new era of big data, one in which artificial intelligence and machine-learning tools are taking center stage in firms’ back offices, a new dynamic is taking shape.

What if the best way to choose investable assets is no longer a binary “yes-or-no” question?

Analytics have been a long been staple of investor decisioning and risk manage-ment, but the new A.I. promises a deeper trove of alternative data, said Celent’s Bailey.

“If you think about what [lenders and issuers] have done with thinking about how they look at credit, how they look at credit rating, how they look at the consumer or other types of credit,” securitization investors can also take the deeper dive different types of machine learning algorithm to gain the same insight, said Bailey.

“You might have found something that, [for example], there’s a 3 percent correla-tion between certain assets. Has that been something investors worry and think about?”

Krubiner said that while big-data analytics is nothing new, what institution-al clients have lacked in portfolio man-agement is collateral context.

The views into underlying assets may be too opaque – or in the case of assets backed by online consumer loans, too new – to properly assess the “value propo-sition” from the buy-side perspective that Pagaya’s platform and its technology seek to attain.

Pagaya’s platform buildout was led by chief technology officer Avital Pardo, who was a data scientist and analyst for small-

biz lender Fundbox. (Pardo deployed A.I. in building a platform that created ability-to-pay projections for small- and medium enterprises, said Krubiner.)

Pardo and Krubiner launched Pagaya in 2016 with another Israeli tech industry entrepreneur, Yahav Yulzari. It was seeded with early investments from the $2.5-bil-lion asset Viola Ventures in Israel. Pagaua received a later investment from retired American Express chief executive Harvey Golub during the firm’s Series B funding in August 2018 (“He literally gave us the first million dollars,” said Krubiner). Golub became a member of Pagaya’s board, which is chaired by Viola Group partner Avi Zeevi.

The faith from early believers in A.I. jumpstarted Pagaya to raise more than $950 million in capital used to acquire its loans, of which more than $515 million have been securitized in private deals via Cantor Fitzgerald. The four deals have made Pagaya a top-10 issuer in the MPL ABS space in 2019. (It’s most recent deal priced in October, topping $200 million in loan-backed securities).

Pagaya had its eye on securitization early by recruiting an asset-backed specialist as its first employee. Benjamin Blatt, a Capital One veteran as well as the former capital markets manager for student-loan refinancing firm Common-Bond, joined the firm in a similar capital markets post for Pagaya in 2017. (He worked out of a shared WeWork space in the same New York building where Pagaya now has its co-headquarters location).

In 2018 Pagaya recruited former BlackRock managing director Ed Mallon as chief investment officer, with plans to expand Pagaya’s investment platform into new asset classes including mort-gages, real estate and auto loans, according to Krubiner.

Adoption growsPetrozzo said AI’s applicability to asset

management was first pioneered in equity trading by firms like Two Sigma Invest-ments, the New York-based hedge fund founded in 2001 which adapted A.I., machine learning and distributed computing into its trading strategies.

“These types of companies sort of set the groundwork for how you can use computers to an advantage… in the buying of securities. But they tend to still be very much on the short-term trade, not on a buy and hold strategy,” said Petro-zzo. “That’s not like how we would how we would think as investors about asset management.”

A.I. is gaining traction in financial services because of the results that financial services firms are reaping from investments in the technology.

In a report earlier this year, Deloitte surveyed 206 global financial institutions on the impact of institutions’ use of A.I. technology (such as advanced analytics, process automation, “robo” advisors and self-learning programs”),

Deloitte found that “frontrunner” institutions in A.I. investments gained 19% returns on their machine-learning outlays compared to 12% for firms that have not adopted these tools as widely.

Deloitte pointed to Nordic bank Nordea as a firm using AI in multiple ways across its organization. The company developed an internal chatbot (“Nova”) which used natural-language processing for responding to online customer queries, and looking at means to automate claims handling, fraud detection and personalizing recommen-dations for clients.

Industry adoption is also easier because the barriers for entry have dissolved for upstart tech firms. The massive investments in computing power and storage has shrunk with the availabil-ity of affordable cloud services, noted Bailey. “All the limitations that existed even five years ago are gone,” said Bailey. “If you have a good data set, you can run.” ASR

“All the limitations that existed even five years ago are gone,” said Bailey. “If you have a good data set, you can run.”

010_ASR1119 10 11/19/2019 8:59:27 AM


How BNY is going further on AIWhile several traditional banks are testing artificial intelligence, BNY Mellon says it’s going further than most, committing to the technology by involving it in multiple aspects of its business.

“We’re not experimenting with AI, we’re really doing it,” said Roman Regelman, senior executive vice president and head of digital for the bank.

Among other things, BNY Mellon has deployed 300 bots using robotics process automation software from Blue Prism. While some purists do not consider them full-fledged AI, bots are widely seen as a low-IQ form of AI that automate simple tasks previously performed by human beings. At BNY Mellon, the bots are deployed across businesses and functions and execute about 5 million processes.

“These robots are doing manual work,” Regelman said. “They’re doing stuff that humans can do, but don’t like to do, and often don’t do that well. That allows the humans we have, the employees, to spend time on more value-added activities, like spending time with clients and spending time on more complicated cases.”

Analysts have taken note. “BNY Mellon is a more visible part of the big-bank pack who three or four years ago were just reaching the point of 100 bots each of varying sophistication in proofs of concept, alpha and beta tests,” said David Weiss, principal analyst at Market Structure Metrics.

While several traditional banks are testing artificial intel-ligence, BNY Mellon says it’s going further than most, committing to the technology by involving it in multiple aspects of its business.

“We’re not experimenting with AI, we’re really doing it,” said Roman Regelman, senior executive vice president and head of digital for the bank.

Among other things, BNY Mellon has deployed 300 bots using robotics process automation software from Blue Prism. While some purists do not consider them full-fledged AI, bots are widely seen as a low-IQ form of AI that automate simple tasks previously performed by human beings. At BNY Mellon, the bots are deployed across businesses and functions and execute about 5 million processes.

“These robots are doing manual work,” Regelman said. “They’re doing stuff that humans can do, but don’t like to do, and often don’t do that well. That allows the humans we have, the employees, to spend time on more value-added activities, like spending time with clients and spending time on more complicated cases.”

Analysts have taken note. “BNY Mellon is a more visible part of the big-bank pack who three or four years ago were just reaching the point of 100 bots each of varying sophistication in proofs of concept, alpha and beta tests,” said David Weiss, principal analyst at Market Structure Metrics. – Penny Crosman

011_ASR1119 11 11/19/2019 8:59:29 AM

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TRADE IDEA GENERATION Research the entire loan universe in real timeFind assets that meet multiple criteria, from issuer to price, yield and credit rating. Virtus Glide technology communicates with our comprehensive repository of proprietary data on the broadly syndicated loan universe and integrates with your third-party data provider of choice.

COMPLIANCE TESTINGManage compliance from your desktopUpon identifying target loans, use Glide to make complex, multi-loan inquiries as to whether certain transactions will meet your loan- and portfolio-level requirements. Receive immediate feedback, eliminating the need to rely on the timeliness and accuracy of analyst models. Glide works seamlessly with BMS and other order management systems. Glide puts the compliance function at your fingertips, so you can know in real time which trades will qualify.

ORDER MANAGEMENTRoute trades through your customized approval processGlide integrates with multiple administration and accounting systems, allowing you to utilize a single order management platform across all of your funds. Glide can be configured to adhere to your specific internal order approval process and can accommodate as many checks and balances as you need. Trade approval workflows can be directed internally or externally to your trustee. Checks can be manual, automatic or a combination of the two.

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013_ASR1119 13 11/14/2019 4:50:56 PM


In September, longtime CLO equity invest-ment firm Tetragon Credit Partners expanded its reach into the market with a decision to add CLO debt purchases to its shopping list.

Since 2004, Tetragon had invested more than $2.4 billion across 105 actively managed collateralized loans, providing the firm and its clients returns on the controlling shares of broadly syndicated loan portfolios involving 32 different managers.

Scott Snell, portfolio manager for Tetragon Financial Group and one of the firm’s three principals, discussed the new strategy as well as observations of the 2019 CLO market and his 2020 issuance and market-trend outlook.

ASR: What is the driving the decision to expand beyond what has been the traditional control-equity stakes?Snell: Tetragon has been getting more inbound investor requests, specifically in CLO mezzanine debt. For buy-and-hold investors, CLO debt offers a differentiated profile typically providing stable income and credit ratings, which is important to some investors. We also think there are times when the market is more volatile where active trading strategies present attractive total return opportunities. By taking our expertise in CLO equity and applying it to building portfolios in the CLO debt space, Tetragon believes it can

deliver exceptional overall value to our investor base. Our success will be driven by strong manager relationships, a deep under-standing of the legal documents, and our ability to select the best risk adjusted credit portfolios.

Any particular reason why minority-equity investing may be more attractive now? When buying minority equity, an investor gives up control of some of the optionality or voting rights that one has as a majority equity investor. It is a different type of analysis and the opportunity has to be more compelling in terms of the risk/reward characteristics. We think the additional yield pickup from minority equity can make sense, but we do think control matters so the risk premium that we demand is definitely higher for minority equity.

Can you can give an overview of what you see in the market for some of those lower-rated mezzanine and subordinate CLO debt tranches? Recently we have seen increased selling in the secondary market of triple-B and double-B-rated paper. The market is starting to differentiate based on perfor-mance, underlying credit quality and how managers are reacting to market conditions. This year a few loans have had violent price movements on the back of missed earnings or some type of restructuring event. With stress

CLO

Q&A: Tetragon’s debt play

By Glen Fest

Firm will complement its equity strategy by adding exposure to the debt side of CLO deals

“Right now, I’d say there are a couple of new asset managers looking to add in the CLO market.”

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building in some portfolios, I think the market has generally reacted appropri-ately and we are seeing investors sell out of weaker deals. As a result, the increase in trading activity has created more technical pressure, which has driven pricing wider both in the primary and the secondary market.

So what kind of challenges or maybe even opportunities does that present to CLO managers? Given the growth in the loan market, CLO managers have more opportunities to differentiate performance, whether that’s staying in the larger, broadly syndicated loan universe or taking more liquidity risk by buying smaller loans. I think with some of the price action you’ve seen this year and continued retail outflows, it’s really given managers the ability to trade around their portfolios and to move into either higher-rated credits or names where they have strong conviction. We think it’s an environment that is ripe for CLO managers with good credit-picking skills to differentiate themselves in terms of spread, price and ratings in their portfolios.

How is the current investor base impact-ing the issuance volume in CLOs and perhaps even how the deals have been structured? There is a stable investor base that is always looking to participate either in the secondary or the primary market. But really, what drives spreads tighter or wider is determined by the marginal investor. Over different periods of time, you’ll see large banks come in and out of the market (particularly in triple A’s), or it could be certain insurance companies or overseas institutional investors. Right now, I’d say there are a couple of new asset managers looking to add in the CLO market. However, given what’s happened with rates, there has been a preference among the asset-manager community to

be less invested in CLOs and more exposed to traditional fixed-income products like investment-grade corporate bonds. You haven’t seen as much of that marginal demand from newer investors, which is why CLO liability spreads are relatively wide. And I think given some of the increased focus on what’s happening to the loan market and negative idiosyn-cratic credit stories, overall demand has been more tepid this year than in the recent past.

Is manager tiering as pronounced toward the end of the year; or are more investors maybe becoming more comfortable with these new managers coming on board? You really have to bifurcate the new-man-ager universe. There are a few new managers that have come to market with very strong capital backing and experi-enced teams. In many cases, they have already issued two or three transactions which have been received well by the market. On the other hand, there are other newer managers that might not be as well established nor have as strong of a track record. We have seen those new managers struggle as the market has demanded higher liability spreads, which makes it very challenging for the arbi-trage to work.

I think to the extent the market becomes more friendly and you do see a pickup in demand particularly for triple As, that dynamic could change. But right now, it’s fairly difficult. Does that bifurcation [on pricing] for the triple-A level, does that also manifest itself in the mezzanine and subordinate tranches and even the equity stakes? Definitely you see bifurcation down the stack. Investors will typically use a similar framework to assess risk in mezzanine tranches as they do for senior debt. Tiering and pricing levels will depend on a variety of factors, including the manager’s default track record, team experience and

portfolio characteristics. In some cases, the frequency of issuance and size of platform can also create a negative supply technical, which may impact spreads. For equity tranches, investors typically try to find managers with a similar outlook on the market and risk tolerance. Every equity investor has different hot button issues that they focus on. For us, we emphasize the manager’s expertise and track record, the positioning and spread of the portfolio, and also the team’s experience with managing CLO structures. Of course, the overall econom-ics will also determine how an equity investor views a particular transaction.

Is tiering driven more by return perfor-mance or overall management skills? Certainly past performance and track record are important when evaluating a management platform. However, there are other factors to consider such as the tenure of the team, compensation structure, and the type of organization. Additional considerations include the risk profile of the portfolio, credit rating distribution, the diversity score and weighted average spread of the underly-ing assets.

It also is important for investors to consider manager styles. The market has gravitated towards more conserva-tively positioned portfolios, given the recent volatility and some of the concerns about where we might be headed in terms of the economy. However, some investors have shorter holding periods and may focus less on the long-term credit outlook if they intend to sell in three to six months. Deal documents and legal language have also become a bigger focus. Some investors are more concerned about getting certain terms, particularly around Libor replacement language. This type of deal term can override manager tiering criteria, especially for some of the largest AAA buyers. ASR

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Despite legal tussles a few years ago over asset transfers from leveraged-loan collateral packages, only a small percentage of lenders have actively sought to block such moves in document contracts.

According to a recent report from S&P Global Ratings based on the rating agency’s review of deals across multiple sectors, only 17% of lenders have provisions that would disallow borrowers from using subsidiaries to transfer collateral assets – such as brands and intellectual property rights – outside lenders’ reach.

Transferring assets became a controversial move after retailers J. Crew and PetSmart

used weak covenants in credit agreements to shift intellectual property to other assets – in both cases for initial public offerings of subsidiary brands that could provide cash needed to tackle the high-leverage woes for the parent firms with near-default ratings.

Moody’s Investors Service described the two firms as “infamous” for “aggressively” moving key brands into unrestricted subsidiar-ies. But perhaps one reason for the current-day low percentage of so-called “J.Crew blockers” may be the success that the issuers ultimately had in satisfying their creditors and ratings agencies.

J. Crew’s planned IPO of Madewell and

PetSmart’s successful IPO of Chewy are credit positive for the companies’ lenders because they will use the proceeds to reduce debt,” said Moody’s in an Oct. 10 report that appeared to vindi-cate the tactic.

Rescue via IPOIn June of this year, PetSmart

raised nearly $900 million from the IPO for Chewy.com, its subsidiary it acquired a year earlier for $3 billion and financed with nearly $2 billion in secured and unsecured debt.

PetSmart had earlier trans-ferred nearly 37% of its stake in Chewy to an unrestricted subsidiary investor group ahead of the IPO.

The money raised from the IPO allowed PetSmart to pay down debt by 15%, according to S&P, as well as see a price boost to its struggling high yield bonds that returned to par pricing in the secondary market, per Bloomberg. PetSmart’s corporate rating benefited, too, being raised to B3 from Caa1 by Moody’s and to B- from CCC by S&P.

The struggling J. Crew chain (which carries a corporate rating of Caa2 from Moody’s and CCC by S&P) is planning an IPO as well for its Madewell brand. According to a September regulatory filing. J. Crew plans to repay debt as well as negotiate new terms on $1.9 billion of its debt due in 2021, according to Moody’s.

CLO

Follow the (J. Crew) blockers

By John Hintze

Despite concerns over tactics that unilaterally remove assets from loan packages, few lenders have sought to block such moves

Weak or nonexistent covenants effectively mean lenders have pre-consented to asset stripping

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(Moody’s stated that in order for the IPO to proceed, J.Crew must still finalize a debt restructuring plan that would provide a settlement of cash and debt-for-preferred equity with consenting lenders).

The IPO filing was preceded by the controversial move in 2017 to shift the Madewell brand into an unrestricted subsidiary that could issue new debt ungoverned by the original J. Crew credit agreements, according to S&P.

Exploiting covenant weaknessAccording to S&P, most provisions

allowing assets to be transferred or disposed traditionally yielded proceeds that were to be used for reducing loan balances or investing in replacement collateral for the secured lenders.

In its report, Moody’s noted however that “[w]eak incurrence covenants enable borrowers to take actions without getting lender consents (or paying economic consideration for such consent),” Moody’s wrote in its report.

“Typical loans now permit issuers to take actions many more actions without paying for the privilege, and investors will experience a rougher ride in stressed deals lacking these guardrails without the cushion that consents and consent fees used to provide.”

Elliot Ganz, the Loan Syndications & Trading Association’s (LSTA) chief of staff and general counsel, said that while he does not condone the transfers, they present a nuanced issue given that, similar to “cov-light” deals excluding maintenance covenants, they give borrowers more flexibility.

“If you look at PetSmart and J. Crew, would you rather have the current outcome or instead have the company with less flexibility and filing for bank-ruptcy?” he said.

Consequently, when the economy sours, there likely will be fewer defaults because of the flexibility provided by

weaker or nonexistent covenants and the ability to monetize other assets, Ganz said.

He noted that lenders tend to consent to changes in their loan agreements since it is typically in everyone’s interest for borrowers to avoid bankruptcy.

However, there’s usually a cost for the borrower and there may be unanticipated changes, such as the lending group becoming more opportunistic and driving harder bargains.

The flip side, he added, is that lenders’ bankruptcy recoveries are likely to be lower than they have been historically. “In the event of default, lenders are probably not going to see recoveries that are 75% to 85% on the dollar.”

Ganz added that the low percentage J. Crew blocker deals found by S&P likely was due to the asset class’s attractive yields and the late stage in the credi cycle, giving borrowers significant leverage in negotiating terms. Neverthe-less, he said, the issue has been highly publicized and the deal terms are transparent, so investors are making rational credit decisions under the circumstances.

Investor concerns still growingS&P noted in its report that courts have

not ruled on the legality of the transfers, since investors’ legal challenges were settled out of court. The report adds that while many loan investors understand the potentially significant risks of IP-leakage risk, also known as “J. Crew blockers.”

Still, a downturn is potentially looming, and refinancing risk increases when the economy sours and lenders pull back. That risk increases further if a borrower’s

valuable assets have been transferred.During the financial crisis, maturities

aligned to create a “refinancing wall” that limited the impact of a large number of borrowers gaining new terms. Today, however, most borrowers have recently refinanced their loans and extended their maturities by several years.

“Maturities have been pushed out, so the reality is there’s very little refinancing risk in the foreseeable future,” Ganz said.

Al Remeza, associate managing director in Moody’s structured finance group, said that the rating agency’s frequent discussions with collateralized loan obligation managers and other loan investors have clearly revealed their “particular concern” about asset stripping.

He added that some say they won’t touch loans with asset-stripping provi-sions, and others, given such language has essentially become standard, focus on names they determine to be less likely to default.

“So there are competitive forces at play here, and clearly investors don’t like it,” he said.

Derek Gluckman, senior covenant officer in Moody’s corporate finance group, noted that weak or nonexistent covenants effectively mean lenders have “pre-consented” to asset stripping or other moves favorable to borrowers that previously would have required lender approval.

In the end, he added, lenders likely would have consented to such moves in many instances, but by pre-consenting they give up any say over those critical decisions and the fees they received for consenting to them.

“Covenants gives borrowers control over when these things happen,” Gluck-man said. “Particularly in a down cycle, lenders get nervous when they start seeing divergence of opinion, but now it’s going to be borrowers controlling the show. ASR

‘Typical loans now permit issuers to take many more actions without paying for the privilege, and investors will experience a rougher ride in stressed deals lacking these guardrails.’

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Golub Capital Partners has priced its first-ever securitization of loans issued through its “late-stage” lending program for promising, venture-capitalized software firms.

The middle-market capital specialist will be collateralizing $340.8 million in loans through a new asset-backed note structure being managed by an affiliate of its middle-market collateralized loan obligation (CLO) manager.

Most of the loans securitized in the Golub Capital Partners ABS Funding 2019-1 portfolio are from the late-stage program that under-writes newly launched firms in the software-as-a-service (SaaS) sector.

Unlike the corporate loans offered through

its standard underwriting, the late-stage loans are for funding VC-backed startup firms that have not yet developed earnings or have low loan-to-value ratios.

The loans to these firms have much lower debt-service levels and about half the LTV ratios of the middle-market firms that Golub traditionally serves.

And Kroll Bond Rating Agency has assessed the loan’s credit quality in the triple-C cat-egory, presenting higher risk and potentially lower recoveries for investors.

But the loans offer investors greater growth opportunities, and Kroll notes the strong per-formance of Golub Capital’s late-stage loan

program since its founding in 2013: zero defaults and no credit losses in the 40 loans issued to date totaling $2.5 billion, accord-ing to Kroll. The loans in the pool are from 37 obligors.

The capital stack includes a $208.57 million Class A notes tranche yielding 4.75% inter-est, with an A rating from the agency. Golub, through its GC In-vestment Management affiliate, will also securitize $133.35 million in subordinate notes.

The report did not state whether those notes would be retained, but issuers of middle-market/small enterprise loans typically retain substantial portions of deals on their books to share “skin in the game” with investors.

GC Investment Management is a unit of GC Advisors, which manages loan portfolios issued through Golub’s middle-market CLO platform.

The deal will launch with a 61% advance rate on the collat-eral. According to Kroll, Golub’s late-stage loans are underwritten to “realized or contractual” recur-ring revenue, rather than earn-ings that are the basis of the its middle-market loans that make up the bulk of activity for the firm, which has over $30 billion in capital under management.

Golub markets the late-stage loans as “flexible credit solutions” that provide working capital for firms without requiring the sur-render of further equity. ASR

CLO

Golub’s SaaSy debut

By Glen Fest

Middle-market lender’s first securitization backed by loans made to VC-funded firms that have yet to generate earnings

Most of the loan were underwritten to newly launched SAAS startup firms

‘Late-stage’ firms have much lower debt-service levels and half the LTV ratios of middle-market firms Golub typically serves.

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As federal regulatory options for fintech firms remain elusive, many in the space are pushing for the creation of an alternative “flexible” supervisory regime that relies on existing au-thorities and a more collaborative approach from state agencies.

The Office of the Comptroller of the Cur-rency has so far been stymied in its attempts to create a national fintech charter, with it planning to appeal a court decision last month that threw out its proposal of the idea. The Federal Deposit Insurance Corp., mean-while, appears to still be debating whether to grant industrial loan company charters to fintech applicants.

That has left the industry, which is currently overseen by dozens of state regulators, seek-ing other options. The Information Technol-ogy & Innovation Foundation, a Washington think tank with a history of tech-friendly policy stances, issued a report in October that included a range of suggestions, includ-ing more multistate compacts and reciprocity agreements among state agencies and the expanded use of no-action letters and regula-tory sandboxes.

But the recommendations face headwinds in the current political environment, with law-makers skeptical of technology firms’ attempts to break into banking.

“There’s a genuine desire among regulators to open the door to allowing more innova-tion within the system,” said Cliff Stanford, a partner at Alston & Bird. “But there are elements of our legal structure that would constrain those efforts without some real change.”

The ITIF argues that when states move together on supervi-sion, innovators with national ambitions can focus on innovat-ing, rather than complying with 50 different state regimes. The report points to Vision 2020, a project launched by the Con-ference of State Bank Supervi-sors last year to streamline the licensing process for fintechs operating across state lines, as one example. “Without a single, comprehensive strategy for financial regulation, regulators will continue to be at odds, and states will continue to pass mis-matched rules that raise costs and reduce consumer welfare,” the report said.

To date, that approach has seen some success in the U.S. — namely with reaching multistate agreements on the use of certain technologies and money trans-mitter licensing — especially when paired with a backstop at the federal level. “Frankly, fintech companies would like to see the efforts on passporting and in the money transmitter space expanded to other product lines,” said John Kromer, a partner at Buckley LLP. ASR

ABS

Flexing on fintech regs

By Brendan Pederson

Thwarted so far at the federal level, financial techcompanies are hoping states will work jointly toward regulatory standards

'Flexible' fintech regulation

More multistate compacts

No-action letters for individual firms

Regulatory sandboxes for new products

Self-regulation

Source: Information Technology & Innovation Foundation

‘Without a single, comprehensive strategy for financial regulation, regulators will continue to be at odds’

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A growing percentage of Santander Consumer USA Holdings Inc.’s subprime auto loans are turning out to be clunkers soon after the cars are driven off the lot.

Some loans made last year are souring at the fastest rate since 2008, with more consumers than usual defaulting within the first few months of borrowing, according to analysts at Moody’s Investors Service. Many of those loans were packaged into bonds.

Santander Consumer is one of the larg-est subprime auto lenders in the market. The rapid failure of some of its loans implies that a growing number of borrowers may be getting loans based on fraudulent applica-

tion information, a problem the company has had before, and that weaker consumers are increasingly struggling. During last decade’s housing crunch, mortgage loans started sour-ing within months of being made.

Subprime car loans aren’t in a crisis, but lenders across the industry are facing more difficulty. Delinquencies for auto loans in general have reached their highest levels this year since 2011.

Santander Consumer had sold to bond in-vestors many of the loans that are going bad. When the debt sours soon after the securities are sold, the company is often obliged to buy the loans back, shifting potential losses to the

original lender and away from bond investors.

“This could eventually be a problem for the company and impact its actual performance,” said Kevin Barker, an equity analyst at Piper Jaffray & Co. Souring loans can cut into profit-ability, he said, adding that the company can raise its lending standards to reduce losses on new financing it provides.

A Santander Consumer USA spokeswoman said the firm’s asset-backed securities per-formance has been consistent over time, and are structured with credit enhancement levels that are appropriate for the risk profile of the securitizations. The firm “does repurchase loans from its securitizations for various reasons, which have been con-sistent over time and in line with the requirements of our transac-tions,” she said.

On earnings calls this year, ex-ecutives at Santander Consumer have said that the company is less likely to cut deals with bor-rowers that fall behind on their obligations now. That results in the lender writing off more bad loans, but also cuts the balance of troubled credits it is looking to restructure.

Chrysler TieSantander Consumer had $26.3 billion of subprime auto loans as of June 30 that it either owned, or bundled into bonds, according to a report from S&P Global

ABS

Speedbump in subprime Santander Consumer sees uptick in subprime auto loans, with more than usual defaulting within months

Rising losses may be a sign weaker borrowers are having financial troubles

“The situation is somewhat perverse in that bondholders are acutally benefiting from high early-payment defaults...”

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Ratings. That represents nearly half of the company’s total managed loans. The percentage of borrowers behind on their loans climbed to 14.50% from 13.80% a year earlier for the loans the company collects payments on, S&P said.

The uptick in delinquencies and de-faults may be tied to Santander Consum-er’s efforts to win more business from Fiat Chrysler Automobiles NV after tighten-ing its longtime financing partnership with the carmaker in July. The updated agreement, which included a one-time payment of $60 million from Santander Consumer to Fiat Chrysler, came after the carmaker’s chief financial officer had said last year that his company was looking at forming its own U.S. financing business.

But the rising losses may also be a sign that the weakest borrowers are having growing financial trouble as economic growth shows signs of slowing. The per-centage of borrowers at least 90 days late on their car loans is broadly growing, ac-cording to data from the Federal Reserve Bank of New York. At the end of 2018, the number of delinquent loans exceeded 7 million, the highest total in the two de-cades the New York Fed has kept track.

Lowering Standards?Lenders don’t seem to be broadly tightening standards in response. About 21% of new auto loans made in the first half of this year went to subprime borrowers, a slight increase from last year.

Banks and finance companies are also making longer-term loans for cars. The average term reached a record high 72.9 months in the second quarter for sub-prime new vehicle loans, according to Ex-perian. Some loan terms have increased to 84 months, in both prime and subprime auto ABS deals. That can weaken auto-bond performance when credit conditions sour, according to a report from S&P.

There are signs that Santander Consumer in particular has eased some underwriting practices. For a roughly $1

billion subprime auto bond that priced earlier this year, Santander Consumer ver-ified fewer than 3% of borrower incomes, even though income verification is a criti-cal way to combat fraud. In comparison, a competitor, GM Financial, verified 68% in one of their bonds.

Some of its struggling loans were bundled into its main series of bonds backed by subprime auto loans. The lender has had to buy back more than 3% of the loans it packaged into some of those bonds, according to a Bloomberg analysis of publicly available servicer reports. Most of those repurchases were because they defaulted early, according to Moody’s. That’s more than Santander Consumer bought back before and higher than industry standards, according to Moody’s analysts.

Settlement RequirementWhile Santander Consumer has generally chosen to repurchase loans that defaulted early, it was required to do so in deal documents following a settlement with Massachusetts and Delaware in 2017.The states alleged that it facilitated high-cost loans that it knew, or should have known, were not affordable for borrowers.

Santander Consumer is the only sub-prime auto asset-backed issuer that has contractually made this promise. The loan buybacks have recently ticked up.

For another series of bonds, those backed by loans to some of the riskiest subprime borrowers, Santander Consumer had to buy back even more loans. For one bond sold about a year ago, around 6.7% of the loans have been repurchased so far, mostly in the first few months after issuance, according to a Bloomberg analysis. That’s higher than average for a deep-subprime auto lending business, ac-cording to PointPredictive, which consults on fraud to banks and other lenders.

Defaults, FraudDuring last decade’s housing bubble, early

defaults began creeping higher around 2007. Now, as then, the rapid defaults may reflect borrowers who should have never received loans in the first place, said Frank McKenna, chief fraud strategist at PointPredictive.

“We’ve always drawn a link between EPDs and fraud,” McKenna said, referring to early payment defaults. “We found that depending on the company, between 30% to 70% of auto loans that default in the first six months have some mis-representation in the original loan file or application.”

Even so, Santander Consumer’s re-purchases of loans packaged into bonds highlights how investors are often insu-lated from some losses on the underlying debt. The portfolio backing Santander Consumer’s asset-backed securities from 2018 actually performed better than deals from the previous two years because the company stepped up its repurchases of early-payment-default loans.

“The situation is somewhat perverse in that bondholders are actually benefiting from high early-payment defaults through the repurchases,” said Moody’s analyst Matt Scully.

The bonds have other protections built into them to withstand stress. For example, the securities may be backed by extra car loans beyond the face value of the notes issued, which can help ab-sorb losses from bad loans. Santander Consumer is the biggest securitizer of subprime auto loans, having sold close to $70 billion of bonds backed by subprime car loans since 2007, according to data compiled by Bloomberg.

But any losses don’t just disappear: in the end, if there are enough, Santander Consumer and bondholders can suffer.

“The weakening performance in the managed portfolio signals elevated risks and is overall a negative development,” said Moody’s analyst Ruomeng Cui in a telephone interview. ASR

Bloomberg News

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JPMorgan is turning to the credit-risk transfer securitization model in a new $757.2 million securitization of prime-quality residential mortgages that it will retain on its books.

According to Fitch Ratings, Chase Mort-gage Reference Notes 2019-CL1 is Chase’s first synthetic credit-linked note transaction, al-though it follows in the footsteps of two earlier post-crisis deals sponsored by Chase aimed at reinvigorating the private-label residential mortgage-backed securities market.

Chase 2019-CL1 will be structured to sell notes that are tied to a reference pool of 979 residential mortgage loans – all of which will remain on JPMorgan’s books rather than

being transferred to a trust.Fitch is not rating the Class A-1R notes

totaling $697.6 million, but assigned ratings to five classes of mezzanine notes, including a $35.9 million Class M-1 tranche at AA.

The model will be able to expand the inves-tor base for the notes, as well as potentially give JPMorgan a way to receive favorable capital treatment while maintaining prime-mortgage assets on its books, according to analysts.

The transaction is similar to the GSE credit-risk transfer platforms – Fannie Mae’s Connecticut Avenue Series and Freddie Mac’s Structured Agency Credit Risk program. JPM-

organ will make payments on the CL1 transaction to the note hold-ers based on the interest rate on the CL1 notes and principal payments are determined based on the actual principal payments received and performance of the reference pool.

This differs from the CAS and STACR transactions that rely on funding sitting in a custodial account to pay interest and principal on the GSEs’ notes. “The highest rating achievable will be linked to [JPMorgan], as well as the credit enhancement required through subordination,” said Susan Hosterman, a Fitch analyst, in an interview.

The notes are general unse-cured obligations of AA-rated JP Morgan.

Hosterman noted that JPM-organ has active in structuring transactions aimed at re-invigo-rating the private RMBS market, which has remained moribund since the housing crisis in 2007 and the ensuring financial crisis. For example, it launched its L Street Securities credit-risk trans-fer deal in 2014, and in 2016 the Safe Harbor CMT transactions, which aimed to comply with the conditions set forth in the Fed-eral Deposit Insurance Corp.’s Safe Harbor Rule.

“Some investors may not be comfortable investing in [private] RMBS, but this allows them to invest in RMBS collateral without investing in a securitization,” Hosterman said. ASR

MBS Report

JPMorgan’s CRT play

By John Hintze

The notes in the deal are structured to reference a pool of 979 resi-dential mortgage loans to remain on the bank’s own books

JPMorgan’s new program is similar to GSE credit-risk transfer programs

The model will be able to expand the investor base for the notes, plus potentially give the bank favorable capital treatment

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When it comes to possible new competitors in the secondary market, the heads of the two current outlets said they more than welcomed the possibility of additional players in their space.

“Bring it on,” Hugh Frater, CEO at Fannie Mae, declared during the Mortgage Bankers Association’s annual convention in Austin, Texas. “We welcome the competition, it uni-formly makes things better.”

But these new players should have to oper-ate under the same rules that Fannie and Freddie Mac do and serve all aspects of the market, he added.

Ending the conservatorships will benefit

both companies, said Freddie CEO David Brickman.

“Outside of conservatorship, we would be able to offer much more,” he said.

Depending on the outcome, Freddie may be able to better serve affordable housing needs and innovate more once conservator-ship ends, Brickman said.

But the utility model some housing reform commentators’ advocate for wouldn’t work, according to Freddie Mac’s CEO.

“We’re not the water company, we’re more complicated than that,” Brickman said.

With the regulations on guarantee fee charges, there is already a form of the utility

model in place, said Frater. But there is a difference; the aim of regulating what the electric com-pany charges is so that consum-ers don’t get overcharged, but the goal in regulating g-fees to ensure that they don’t get under-charged, Frater said.

What will not change is Fan-nie Mae’s commitment to its customers and its commitment to affordable housing, he said.

The two heads of the govern-ment-sponsored enterprises said they believe they will be able to work with the Federal Hous-ing Finance Agency to turn the government’s set of principles regarding housing finance reform into a plan for post-conservator-ship reform.

“We think we have a viable business that private capital will be attracted to,” Brickman said.

An early October announce-ment that Fannie Mae and Freddie Mac will be allowed to keep profits ($20 billion and $25 billion, respecitvely) for the first time since 2012 was seen as a crucial early step in reforming the mortgage giants.

But the news immediately shifted focus to a bigger question about their financial standing. Ending the “net worth sweep” improves Fannie and Freddie’s capital only in the short term. The news had many observerses-timating capital needs of $100 and $200 billion each to be sustainable. - with reporting from Hannah Lang. ASR

MBS Report

GSEs: ‘Bring on’ competition

By Brad Finkelstein

Housing finance reform could bring new entrants to the secondary market. Fannie and Freddie execs say they welcome the possibility

Fannie and Freddie directors spoke at the MBA convention in Austin, Tex.

Freddie chief executive Brickman: “Outside of conservatorship, we would be able to offer much more.”

BLO

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023_ASR1119 23 11/19/2019 8:59:41 AM

At Wilmington Trust, we’ve been working with issuers since the

inception of the securitization market. Your structured fi nance

transaction deserves the attention of a team that has deep

experience as a full-service trustee for all asset classes in the

securitization marketplace. We serve clients across the country and

around the world, providing the trustee and administrative services

required for ABS/MBS transactions.

For more insight on how we’ve successfully assisted clients on

corporate trust transactions, contact one of our experienced

professionals or visit wilmingtontrust.com/structuredfi nance.

PATRICIA [email protected]

302.636.6104

Is your trustee as invested in the structured fi nance market as you are?

Services provided by Wilmington Trust, N.A. Wilmington Trust is a registered service mark. Wilmington Trust Corporation is a wholly owned subsidiary of M&T Bank Corporation. Wilmington Trust Company, operating in Delaware only, Wilmington Trust, N.A., M&T Bank, and certain other a� liates provide various fi duciary and non-fi duciary services, including trustee, custodial, agency, investment management, and other services. International corporate and institutional services are o� ered through Wilmington Trust Corporation’s international a� liates. Loans, credit cards, retail and business deposits, and other business and personal banking services and products are o� ered by M&T Bank, member FDIC. ©2019 Wilmington Trust Corporation and its a� liates. All rights reserved. 36180 191112 VF

T R U S T E E S E R V I C E S | B A C K U P S E R V I C I N G | C L O A N D L O A N A D M I N I S T R A T I O ND O C U M E N T C U S T O D Y | E V A U L T | I N D E P E N D E N T D I R E C T O R | T A X & A C C O U N T I N G

BEN JORDAN [email protected]

410.244.4090

PATRICK TADIE [email protected]

212.941.4407

EXPERIENCEOur

means you’ll have a better one.

RICK D’[email protected]

212.941.4414

024_ASR1119 24 11/14/2019 1:24:37 PM

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