AUG 2007 - Lending Club launches as Facebook app. SEP 2013 - JOBS Act signed into ...... third-party affiliate websites.
Stress Testing
Marketplace Lending in a Rapidly Changing Environment By David Snitkof, Larry Haertel Jr., Raymond Han and Michael Toth Orchard Platform
INTRODUCTION
CONTENTS Introduction
1
A Brief History of Marketplace Lending
4
Methodology
6
Stress Testing
9
Analysis of Historical Originations
12
Benchmarking Against Other Asset Classes
14
Management of Risk in Anticipation of Stress
16
Conclusion
20
In an era of Federal Reserve near-zero interest rate policy and with
The question that seems to be on everyone’s mind is, what happens
bond markets near historically low yields, marketplace lending
then? How might higher unemployment levels, falling home
has emerged as a new asset class with attractive returns and low
prices, and credit deterioration affect the returns of loan portfolios
volatility. Over the last five years, we’ve seen strong and consistent
originated under the marketplace model? How much stress would
returns from portfolios of marketplace loans. The Orchard
be needed to realize negative returns? What can we expect? In
Consumer Marketplace Lending Index presents a compelling
this paper, we will define a framework for stress testing, simulate a
picture of the potential returns of this new asset class, with 2015
range of outcomes, and provide expectations and guidance on the
returns that have clearly outperformed stalwarts such as the
expected returns of marketplace loans through a series of stressors.
S&P 500 and the Barclays Aggregate Bond Index. While falling unemployment rates and strong domestic growth have provided the ideal opportunity for this new asset class to flourish, we know that these favorable conditions cannot last forever.
105%
100%
95%
AGG: ISHARES BARCLAYS AGG. BOND FUND HYG: ISHARES HIGH YIELD CORP BOND ETF ORCHARD CONSUMER LENDING INDEX SPY: SPDR S&P 500 TRUST ETF
90% JAN 2015
FEB 2015
MAR 2015
APR 2015
MAY 2015
JUN 2015
JUL 2015
AUG 2015
SEP 2015
NOV 2015
INTRODUCTION
Two predominant business models prevail: non-bank balance-sheet
Fundamentally speaking, a marketplace-funded loan is no different structurally from a loan funded through other means. All other things being equal, a borrower making a loan payment wouldn’t care whether that loan is held on a lender’s balance sheet or if it is sold to a hedge fund, business development company, or family office. And yet, the question of how “marketplace” loans will perform in various economic environments persists. There are multiple reasons for this, which span the areas of industry dynamics, operational capacity, and consumer psychology.
A Brief History of Marketplace Lending
lenders and marketplace lenders. On the one hand, balance-sheet lenders behave a lot like traditional lenders, funding loans using their own balance sheets, but they use elements of novel technology to make faster and better credit decisions, offer a more seamless borrower experience, or integrate deeper with their customers’ financial lives. On the other hand, marketplace lenders use a digital marketplace to match borrowers and lenders, assuming little to no balance-sheet risk. Given that both models have merit and have experienced success, some platforms now employ a hybrid model. While borrowers created the need for these platforms, it has really been the investors - those funding the loans - who have propelled the industry forward. Marketplace lending, originally
First, the originators and servicers (often the same entity) engaged in
disadvantage as against an issuer with multiple product lines. For
this new world of marketplace lending are relatively new and may
instance, borrowers may be more reluctant to miss a payment on
not have the same track record or recession-hardened perspective
a loan from an institution where they have additional financial
held by more traditional lenders. Some industry participants may
products, such as a deposit account or credit card.
worry about how the underwriting, servicing, and collections practices of these newer entities would hold up in a challenging
Finally, it is necessary to consider the consequences of defaulting
environment, with increased pressure on their operational capacity.
on different loan obligations. With marketplace loans, the main
There is also some concern that originators chasing increasingly
consequence is credit score deterioration. For secured loans such as
ambitious growth targets would be hesitant to recalibrate risk
a mortgage or an auto loan, a default can result in the loss of the
policies in a way that would put that growth story in jeopardy.
underlying collateral. In the case of credit cards, the most common
In an environment with a higher rate of missed payments and
form of unsecured lending, although there is no pledged collateral,
financial difficulty for borrowers, organizations would also need
there is what can be thought of as an opportunity cost of default. If
to scale up their servicing and collections capabilities, which have
forced to choose between making a payment on a term loan or on
largely been built in a lower-stress environment and not subject to
a revolving line of credit, a stressed borrower may opt to keep the
major capacity challenges.
revolving line current in order to preserve future purchasing power.
Next, the new breed of marketplace lender tends to be a monoline
As marketplace lending continues to grow and encompass a greater
issuer, and the most prevalent product offered today is the fixed-rate
share of financial activity in the U.S. and around the world, these
amortizing term loan. Both of these attributes present challenges
questions will become increasingly important. More time and
to what is known as the payment hierarchy—the order in which
experience in diverse market conditions will provide more of the
a borrower decides to pay his or her debt obligations in a time of
data needed to answer them.
financial stress. A monoline issuer, in this case, is at a theoretical
3
Orchard Platform
Marketplace lending has come to encompass a number of different
labeled “peer-to-peer”, or “P2P,” lending, consisted of groups of
business models, but at its most basic, it involves the investment
individual retail investors lending to individual borrowers. However,
of capital via data-driven online platforms to lend directly and
this symbiotic relationship has experienced a pronounced and
indirectly to borrowers. A marketplace-lending loan is generally
seemingly permanent shift as institutional investor interest in the
a short-duration, high-yielding, fixed-income instrument. The
space has ballooned in recent years. This trend may be attributed
marketplace-lending loans available today are predominantly
to to a variety of factors, including a low-interest-rate environment,
unsecured consumer loans and secured and unsecured small-
increased transparency and availability of data, and attractive risk-
business loans, though we are seeing growth across a wide array
adjusted returns.
of asset classes including student, mortgage, auto, and invoicefactoring loans.
Meanwhile, banks, which had for the most part dismissed marketplace lending as a transient movement, now view the industry
Marketplace lending largely began in the United Kingdom with
as scalable and enduring and are racing to leverage the technology
Zopa in 2005 and arrived in the United States shortly thereafter
of its leading platforms. One prominent example is the recent
with Prosper Marketplace and Lending Club. The idea behind
partnership between JPMorgan Chase & Co. and OnDeck Capital.1
these early platforms was novel: Reimagine the business of credit by
In other cases, banks such as Goldman Sachs are attempting to
cutting out the middlemen and letting individuals lend to each other
build their own technology-enabled consumer and small-business
through more efficient online markets, thus providing lower rates
lending platforms.2 Banks are also helping to facilitate leverage and
to borrowers than offered by traditional banks and better returns to
securitizations for some lending platforms, fueling further growth
investors. Many of these platforms emerged from the turmoil of the
for the industry. In addition, we recently witnessed a number of
2008 financial crisis, extending much needed funding for consumers
platforms execute successful IPOs, such as Lending Club and
and small businesses who had been almost completely shut off from
Ondeck, the former having conducted the fourth largest IPO in
traditional lending channels. Since then, a multitude of platforms
U.S. Internet history. Several other platforms have announced their
has sprouted up, offering a wide range of products and solutions to
intentions to issue public offerings and are currently in the queue
an even more diverse group of borrowers.
waiting for adverse market conditions to subside.
Stress Testing
4
METHODOLOGY
2005
MILESTONES
MARCH 2005 Zopa launches in U.K.
IN MARKETPLACE LENDING
Recently, regulators have expressed heightened interest in marketplace lending, as it has become an increasingly
FEB 2006 - Prosper launches in U.S. MAY 2006 - OnDeck launches in U.S.
meaningful part of the financial services landscape. Last summer, the U.S. Department of Treasury issued a
2007 AUG 2007 - Lending Club launches as Facebook app OCT 2007 - Dow Jones Industrial Average peaks
Request for Information seeking input from leading industry participants and stakeholders. Policymakers are using this information to study the growing number of business models and products
SEP 2008 - Lehman Brothers files for bankruptcy
offered by marketplace lenders, the potential for online marketplace lending
2009
to expand access to credit to historically MAR 2009 - Dow Jones Industrial Average bottoms out
underserved borrowers, and how the financial regulatory framework should
JUL 2010 - Dodd Frank signed into legislation AUG 2010 - Funding Circle launches small business lending in U.K. DEC 2010 - Prosper drops variable rate model
2011
evolve to support the safe growth of this burgeoning industry.3 As marketplace lending evolves, its potential to transform the global
NOV 2012 - Lending Club surpassed $1B in originations DEC 2012 - Avant Launches
allocation of capital has captured the imagination of an industry. Technology and data are rapidly changing the way lending is done in the U.S. and around the world. While marketplace lending still only accounts for a narrow portion of the
2013 SEP 2013 - JOBS Act
OCT 2013 - Funding Circle launches in U.S. joining forces w/ Endurance Lending Network
DEC 2013 - Orchard Platform launches
S&P and “A2” from Moody’s
/ Eaglewood Capital deliver first p2p securitization
DEC 2014 - Lending Club IPO raises $1B
2015 DEC 2014 - OnDeck MAY 2015 - Avant reaches $1B in loan originations since launching in January 2013
5
insignificant. The future of marketplace be exciting to see what comes next.
NOV 2014 - SoFi achieves ‘A” rating from
OCT 2013 - Lending Club
IPO raises $320M
global credit market, its progress is not lending is sure to be very bright and it will
signed into legislation
Methodology
1. Son, H. “JPMorgan Working With On Deck to Speed SmallBusiness Loans.” Bloomberg, News, Web. 1 Dec. 2015 2. Corkery, M. and Popper, N. “Goldman Sachs Plans to Offer Consumer Loans Online, Adopting Start-Ups’ Tactics.” New York Times, Deal Book, Web. 15 Jun. 2015
To analyze the effects of market stresses on a loan portfolio, it is important to decide upon an agreeable model for projecting future cash flows on loans.
We decided to turn to the standard prepayment-default-recovery model that has been in use for many years in the mortgage and asset-backed securities markets. Next, we established a base case for expected cash flows in a non-stressed scenario. Finally, we stressed our default assumptions in order to get a sense for what we can expect in a stressed scenario. Our cash-flow model has three key inputs: CPR (Constant Prepayment Rate), CPR =1-(1- Prepayment Amount / (Beginning Balance-Default Amount - Scheduled Principal))^12 CDR (Constant Default Rate CDR =1-(1- Default Amount / Beginning Balance)^12 Recovery rate (Rec = Recoveries / Default Amount) Each of these input assumptions plays a role in the calculation of monthly cash flows. At the beginning of each projected payment month, a percentage of the pool (corresponding to the supplied CDR) defaults. After that, all survivors in the pool make their scheduled monthly payments. Next, a percentage of the remaining survivors (corresponding to the supplied CPR) prepay their loans in full. Finally, we also receive recovery amounts equal to the supplied Recovery Rate times the dollar amount of defaults this period. We repeat the above process until every loan in our portfolio has fully matured.
3. Treasury Seeks Public Comments on Marketplace Lenders.” U.S Department of Treasury, Press Center, Web. 16 Jul. 2015
Orchard Platform
Stress Testing
6
METHODOLOGY
1. Beginning Balance = $10,000
For our base-case CPR
flows for one month on a hypothetical $10,000 loan pool with a weighted average interest rate of 16% and a remaining term of 36 months. For this example, we’ll use 5% CDR, 15% CPR, 3% Recovery. In summary, under these assumptions, in this
2. CDR = .05 = 1 − 1 − �
�
3. .05 = 1 − 1 − �
�
Beginning Balance
Default Amount 10,000
$124.47 in interest payments, $351.68 in principal payments ($124.47 scheduled principal and $220.71 prepaid principal), and $1.28 in recoveries.
we assume a constant 14.5%
�
based on historical loan data across the consumer unsecured space. Orchard Curves attempt to capture the observed loan seasoning effect whereby charge-offs in static pools ramp
Looking historically, the
4. Default Amount = $42.65
model over historical realized charge-offs
5. Scheduled Payment = Balance *
much less pronounced than it
Interest Rate * (1+Interest Rate)Term
is for CDR, and defaults have
(1+Interest Rate)Term− 1
6. Scheduled Payment = (10000 − 42.65) *
in the consumer lending space from 2010 to the present. After the initial fitting of the curves, they are scaled to align with recent performance. (The detailed mathematics behind the generation of these curves are beyond the scope of this paper but may be discussed further in future research products.)
7
Orchard Platform
15%
17.5%
7.5%
a significantly larger effect
.16 .16 36 (1 + ) 12 * 12
(1 +
10%
on portfolio yield relative to
.16 36 12 ) -1
5%
prepayments. For Recovery rate, we use the
0
observed average of 3%.
4
8
12
16
9. Scheduled Interest = (10000 −42.65) *
.16 12
= $124.47
20
24
28
32
36
Months on Book
8. Scheduled Interest = (Beginning Balance − Default Amount) * Interest Rate 60 Months Loans Model CDR Interest Rates
10. Scheduled Principal = Scheduled Payment − Scheduled Interest
12.5%
>= 20%
= 20%
over our analysis period.
For our base-case CDR (charge-off) curves (hence referred to as Orchard Curves)
< 7.5%
20%
observed long-term average
�
7. Scheduled Payment = $345.17 expectations, we have generated charge-off
Interest Rates
CPR for simplicity. This is the
�
�
month, $42.65 of our portfolio would have charged off, and we would have received
12
(prepayment) expectations,
12
Default Amount
36 Months Loans Model CDR
CDR
Let’s look at an example of how to project cash
10%
�
14. Prepay Amount = $130.98 15. Recovery Amount = Recovery * Default Bal 16. Recovery Amount = .03 * 42.65 = $1.28
5%
0 4
8
12
16
20
24
28
32
36
40
44
48
52
56
60
Months on Book
Stress Testing
8
STRESS TESTING
Stress Testing Now that our model and default assumptions have been established, we will combine
With our base case assumptions, our static market portfolio is expected to realize a 6.7%
them and generate a set of hypothetical base-case future cash flows. The portfolio
yield, a duration of .88 years and a weighted average life of 1.62 years. All calculations
of loans for which we are projecting cash flows comprises all loans in our data set
above are based on a purchase price of par (or face value). What happens if, over the life
originated in Q3 2015. These cash flows will then be analyzed to develop a set of static
of the portfolio, the realized defaults are double the expected defaults? In that case, our
pool performance metrics. The quarterly cash flows are as follows:
cash flows will be as follows:
Period
BegBalance
ChargeOffs
Recoveries
Interest
Serv_Fee
Sched_Principal Unsched_Principal EndBalance
Period
BegBalance
ChargeOffs
Recoveries
Interest
Serv_Fee
Sched_Principal Unsched_Principal EndBalance
1
$1,000,000.00
$-
$-
$31,792.71
$2,422.81
$54,729.49
$36,997.70
$908,272.82
1
$1,000,000.00
$-
$-
$31,792.71
$2,422.81
$54,729.49
$36,997.70
$908,272.82
2
$908,272.82
$4,124.25
$123.73
$28,847.67
$2,190.79
$54,116.99
$33,394.66
$816,636.92
2
$908,272.82
$8,226.61
$246.80
$28,746.10
$2,184.76
$53,984.91
$33,302.51
$812,758.79
3
$816,636.92
$7,450.10
$223.50
$25,870.47
$1,959.62
$53,268.73
$29,807.89
$726,110.21
3
$812,758.79
$14,704.66
$441.14
$25,523.09
$1,938.85
$52,765.03
$29,491.07
$715,798.02
4
$726,110.21
$9,689.86
$290.70
$22,931.62
$1,733.16
$52,210.65
$26,297.05
$637,912.65
4
$715,798.02
$18,806.00
$564.18
$22,277.80
$1,693.64
$51,136.19
$25,695.82
$620,160.02
5
$637,912.65
$10,878.75
$326.36
$20,082.90
$1,514.36
$50,968.27
$22,907.76
$553,157.87
5
$620,160.02
$20,661.36
$619.84
$19,123.99
$1,455.74
$49,167.59
$22,018.83
$528,312.24
6
$553,157.87
$11,131.10
$333.93
$17,366.33
$1,305.75
$49,578.51
$19,679.08
$472,769.18
6
$528,312.24
$20,614.30
$618.43
$16,149.89
$1,230.64
$46,949.62
$18,544.19
$442,204.13
7
$472,769.18
$10,613.37
$318.40
$14,812.78
$1,109.31
$48,086.67
$16,641.19
$397,427.96
7
$442,204.13
$19,116.84
$573.51
$13,415.41
$1,022.32
$44,583.65
$15,332.74
$363,170.90
8
$397,427.96
$9,521.69
$285.65
$12,441.78
$926.37
$46,543.75
$13,813.95
$327,548.57
8
$363,170.90
$16,651.21
$499.54
$10,953.42
$833.21
$42,173.72
$12,420.69
$291,925.27
9
$327,548.57
$8,063.90
$241.92
$10,261.94
$757.55
$45,004.08
$11,206.56
$263,274.03
9
$291,925.27
$13,676.07
$410.28
$8,773.31
$664.20
$39,820.36
$9,820.88
$228,607.96
10
$263,274.03
$6,446.23
$193.39
$8,272.05
$602.83
$43,523.63
$8,817.75
$204,486.42
10
$228,607.96
$10,594.40
$317.83
$6,865.58
$514.90
$37,616.90
$7,525.76
$172,870.91
11
$204,486.42
$4,865.08
$145.95
$6,462.17
$461.54
$42,159.05
$6,636.45
$150,825.84
11
$172,870.91
$7,741.45
$232.24
$5,206.44
$383.80
$35,648.67
$5,510.91
$123,969.88
12
$150,825.84
$3,504.93
$105.15
$4,814.87
$332.44
$40,967.81
$4,642.60
$101,710.51
12
$123,969.88
$5,391.32
$161.74
$3,761.69
$268.54
$33,995.21
$3,738.52
$80,844.83
13
$101,710.51
$2,597.83
$77.93
$3,574.35
$237.71
$10,777.92
$3,559.88
$84,774.88
13
$80,844.83
$3,865.96
$115.98
$2,702.77
$185.92
$8,467.13
$2,783.81
$65,727.92
14
$84,774.88
$2,049.04
$61.47
$2,957.81
$197.09
$10,479.17
$2,931.44
$69,315.22
14
$65,727.92
$2,966.56
$89.00
$2,177.49
$150.49
$8,034.24
$2,237.96
$52,489.16
15
$69,315.22
$1,553.99
$46.62
$2,397.28
$159.99
$10,203.73
$2,357.74
$55,199.77
15
$52,489.16
$2,193.37
$65.80
$1,721.23
$119.45
$7,645.15
$1,759.88
$40,890.76
16
$55,199.77
$1,120.89
$33.63
$1,886.94
$126.10
$9,953.94
$1,833.43
$42,291.51
16
$40,890.76
$1,545.98
$46.38
$1,324.05
$92.21
$7,300.48
$1,340.41
$30,703.89
17
$42,291.51
$754.48
$22.63
$1,420.96
$95.05
$9,731.72
$1,353.08
$30,452.22
17
$30,703.89
$1,019.38
$30.58
$976.69
$68.22
$7,000.27
$970.89
$21,713.35
18
$30,452.22
$456.99
$13.71
$993.57
$66.50
$9,538.64
$911.27
$19,545.32
18
$21,713.35
$606.38
$18.19
$670.70
$46.95
$6,744.23
$643.23
$13,719.51
19
$19,545.32
$229.03
$6.87
$599.17
$40.11
$9,376.02
$502.70
$9,437.57
19
$13,719.51
$299.18
$8.98
$398.38
$27.93
$6,532.04
$349.99
$6,538.31
20
$9,437.57
$70.27
$2.11
$232.41
$15.56
$9,245.06
$122.24
$-
20
$6,538.31
$90.57
$2.72
$152.72
$10.72
$6,363.47
$84.27
$-
9
Orchard Platform
Stress Testing
10
STRESS TESTING
Charge-Off Rate Charge-Off Rate
positive at 1.01%. In fact,
10% 10%
rates in order for a loss to be realized. For reference, default rates on credit card receivables peaked in Q2 2010 at 10.97%, which is 2.23 times the average credit card default rate throughout 2000–2007 (4.92%).
Charge-Off Rate On Credit Card Loans Charge-Off Rate On Credit Card Loans
realized defaults would have
Of Historical Originations
8% 8%
6% 6%
In the graph to the right, we
4% 4%
rates of marketplace loans by
2% 2%
annual vintage. We see that 2006, 2007, and 2008 vintages
00
Below is a yield table of
1986 1986 1988 1988 1990 1990 1992 1992 1994 1994 1996 1996 1998 1998 2000 2000 2002 2002 2004 2004 2006 2006 2008 2008 2010 2010 2012 2012 2014 2014
CDR Multipliers vs. CPR
Observation Dates Observation Dates
all experienced substantially higher charge-off rates than
and the resulting yields
those in recent years, which
of each scenario. Red
are clustered together near the
highlighted scenarios represent negative yield.
CPR
1
1.25
1.5
1.75
2
2.25
2.5
2.75
3
12
6.63%
5.21%
3.82%
2.45%
1.11%
-0.21%
-1.51%
-2.79%
-4.04%
12.5
6.64%
5.23%
3.84%
2.48%
1.14%
-0.17%
-1.47%
-2.74%
-3.99%
13
6.66%
5.25%
3.87%
2.51%
1.17%
-0.14%
-1.43%
-2.70%
-3.94%
13.5
6.68%
5.27%
3.89%
2.54%
1.21%
-0.10%
-1.39%
-2.65%
-3.89%
14
4. Source: https://research.stlouisfed.org/ fred2/series/CORCCACBS
Cumulative Rate of Charge-Offs by Vintage for 36 Month Loans 30%
plot the cumulative charge-off
6.69%
5.29%
3.92%
2.57%
1.24%
-0.06%
-1.35%
-2.61%
-3.85%
14.5
6.71%
5.31%
3.94%
2.60%
1.27%
-0.03%
-1.30%
-2.56%
-3.80%
15
6.72%
5.33%
3.97%
2.63%
1.31%
0.01%
-1.26%
-2.51%
-3.75%
15.5
6.74%
5.35%
3.99%
2.66%
1.34%
0.05%
-1.22%
-2.47%
-3.70%
16
6.76%
5.38%
4.02%
2.69%
1.38%
0.09%
-1.18%
-2.42%
-3.65%
16.5
6.77%
5.40%
4.04%
2.71%
1.41%
0.13%
-1.14%
-2.38%
-3.60%
17
6.79%
5.42%
4.07%
2.74%
1.44%
0.16%
-1.09%
-2.33%
-3.55%
17.5
6.81%
5.44%
4.09%
2.77%
1.48%
0.20%
-1.05%
-2.28%
-3.50%
18
6.82%
5.46%
4.12%
2.80%
1.51%
0.24%
-1.01%
-2.24%
-3.45%
bottom of the graph. To provide additional detail on
% of%Vintage of Vintage Charged Charged Off by OffBalance by Balance
undoubtedly lower but still
to be 2.2 times projected
Analysis
Charge-Off Rate On Credit Card Loans, All Commercial Banks, January 1985 to October 2015 4
30%
2006 Vintage
25%
2007 2006 2008 2007
25%
2009 2008
20%
2010 2009
20%
2011 2010
15%
2012 2011
15%
2013 2012
10%
2014 2013
10%
2015 2014
5%
2015
5% 0
vintages, we’ve also created the
4
8
12
16
4
8
12
Months Since 16 20 Origination 24
20
24
28
32
36
28
32
36
Months Since Origination
chart below, which removes the 2006–2008 data. Here, we
Vintage
0
charge-off performance in later
Cumulative Rate of Charge-Offs by Vintage for 36 Month Loans, 2009 - Present
see steady improvement, with
10%
Vintage
vintages 2013–2015 showing
10%
2009 Vintage
the lowest cumulative charge-off rates to-date of all vintages.
% of%Vintage of Vintage Charged Charged Off by OffBalance by Balance
Our yield in this scenario is
ANALYSIS OF HISTORICAL ORIGINATIONS
2010 2009 2011 2010
7.5%
2012 2011
7.5%
2013 2012 2014 2013
5.0%
2015 2014
5.0%
2015
2.5% 2.5% 0 0
4
8
12
16
4
8
12
Months Since 16 20 Origination 24
20
24
28
32
36
28
32
36
Months Since Origination 11
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ANALYSIS OF HISTORICAL ORIGINATIONS
BENCHMARKING AGAINST OTHER ASSET CLASSES
The table below demonstrates the changes in borrower characteristics for this asset class across
What explains this performance? In particular, why
the past 10 years. In the first few years, we saw yearly originations of less than $100M, with
do 2006–2008 vintages perform so much more
average interest rates in the 16%–18% range and average borrower income of approximately
poorly than more recent ones?
$70K. We also saw small average loan sizes, ranging from $4K–$7K. In more recent years, we see significantly lower average interest rates and much higher average borrower incomes and average loan sizes. It’s worth mentioning that the income growth we are seeing is real; even after
One possible explanation is the financial crisis
accounting for wage inflation, we notice a material increase in average incomes over time.
in 2007–2008. During this period, performance
Vintage
Avg_loan_amount Avg_term
Avg_rate
Avg_income
Avg_dti
industry, which is why we should also expect to see
2006
$4,780.55
36 Mos
17.86%
$72,682.73
20.58%
2007
$7,040.29
36 Mos
16.40%
$72,733.35
25.40%
2008
$6,433.61
36 Mos
15.80%
$71,565.46
22.63%
deteriorated across nearly all sectors of the credit
from marketplace originators. While the credit crisis was clearly responsible for some of the performance differences we
$8,457.04
36 Mos
13.49%
$79,646.07
14.21%
experienced, it does not tell the full story. From
2010
$8,618.07
42.25 Mos
13.46%
$79,461.21
14.90%
2006–2008, marketplace lending was a nascent
2011
$10,305.95
46.00 Mos
14.71%
$81,124.71
16.10%
$12,115.69
43.53 Mos
15.33%
$80,677.49
18.22%
2013
$13,952.39
45.00 Mos
15.09%
$84,183.12
18.76%
2014
$14,308.12
45.99 Mos
14.09%
$87,976.76
20.83%
2015
$14,829.90
45.98 Mos
13.16%
$87,252.15
22.55%
Against Other Asset Classes
higher levels of non-performance among loans
2009
2012
Benchmarking
industry. Total originations in this period were $204M. When compared with originations of over $5B in 2014 alone, we see what a small sample size these first few years represent. The originators were just getting started and had not fully
In the graph below, we show a performance comparison of the
indices become tradable assets, we should expect to see higher
Orchard Consumer Lending Index vs. three market exchange-
levels of volatility in periodic returns, but we would expect similar
traded funds (ETFs), the S&P 500, the Barclays Aggregate Bond
cumulative returns.
Index, and an iShares High Yield Corporates Index. The graph shows the evolution of the portfolio value of an investment begun
The graph shows that marketplace assets have outperformed
on January 1, 2011 in each of these assets. Note that while the
traditional bond investments over this time period, but
Orchard Consumer Lending Index tracks the performance of an
underperformed the S&P equity index. While the above graph
investment in marketplace loans, it is not an investable index like
demonstrates the cumulative performance of asset returns over
the other three represented, and therefore it shows significantly
time, the final result is really a snapshot of one date, which could
lower daily volatility than those assets. Once marketplace lending
be considered somewhat arbitrary.
2.00
developed their underwriting criteria. They were targeting comparatively lower-quality borrowers at higher interest rates. All of these factors would
Comparitive Performance of Marketplace Lending and Traditional Investment Portfolios
also lead to higher charge-off levels as compared to
175%
recent years. Above, we present some stratifications
AGG: iShares Barclays Agg. Bond Fund
across key credit variables by year to demonstrate
HYG: iShares High Yield Corp Bond ETF
the difference in populations receiving loans during
150%
Orchard Consumer Lending Index SPY: SPDR S&P 500 Trust ETF
Portfolio Value
these different periods.
TICKERS
125%
100%
75% Jan 2011
Jan 2012
Jan 2013
Jan 2014
Jan 2015
Date
13
Orchard Platform
Stress Testing
14
75% Jan 2012
Portfolio Value
Portfolio
100% BENCHMARKING AGAINST OTHER ASSET CLASSES
125%
MANAGEMENT OF RISK IN ANTICIPATION OF STRESS
100% 75%
Jan 2013
Jan 2014
Jan 2015
Jan ‘13
Jul ‘13
Jan ‘14
Jul ‘14
Jan ‘15
Jul ‘15
Instead of the 2011–2015 period Date shown, we might consider the
Datein this case the Orchard For 2014, we see a similar result, although
yearly performance for a series of simulated investments made at the
Consumer Lending Index almost matches the returns of the S&P
beginning of each year from 2012 through 2015, with positions held
500. For investments beginning in January 2015, the Orchard
through 175% the end of 2015. For investments beginning in 2012 and
Consumer 175%Lending Index is the best performing of the four, given
2013, we see a result similar to what was observed above: The S&P 150%
the market turmoil experienced by the S&P over that period. As 150%
shows the best performance, although with higher volatility, and 125%
Portfolio Value
Portfolio
125%
mentioned above, some of the consistency in marketplace lending 125%
the Orchard Consumer Lending Index shows steady appreciation,
performance is because it is not a tradable index and therefore is not
ahead of both the Barclays Aggregate and the iShares High Yield
subject to the daily volatility experienced by the other investments.
100%
75% Corporate Bond ETF. Jan ‘14
Jul ‘14
100% 75%
Jan ‘15
Jul ‘15
Jan ‘15
Jul ‘15
Jan ‘15
Apr ‘15
Date
Jul ‘15
Oct ‘15
Date
Comparative Performance of Marketplace Lending and Traditional Investment Portfolios TICKERS
AGG: iShares Barclays Agg. Bond Fund
HYG: iShares High Yield Corp Bond ETF
Orchard Consumer Lending Index
SPY: SPDR S&P 500 Trust ETF
150%150% 150%150%
150%150% 150%150%
125%125% 125%125% 100%100% 100%100% 75% 75% 75% 75% Jan 2012 Jan 2012 Jan 2013 Jan 2013 Jan 2014 Jan 2014 Jan 2015 Jan 2015 Jan 2012 Jan 2012 Jan 2013 Jan 2013 Jan 2014 Jan 2014 Jan 2015 Jan 2015 Date Date Date Date
125%125% 125%125% 100%100% 100%100% 75% 75% 75% 75% Jan ‘13 Jan ‘14 Jan ‘15 Jan ‘13 Jul ‘13Jul ‘13 Jan ‘14 Jul ‘14Jul ‘14 Jan ‘15 Jul ‘15Jul ‘15 Jan ‘13 Jan ‘13 Jul ‘13Jul ‘13 Jan ‘14 Jan ‘14 Jul ‘14Jul ‘14 Jan ‘15 Jan ‘15 Jul ‘15Jul ‘15 Date Date Date Date
2015
Investors rely on their attitudes about the future to make decisions
which is relatively simple for institutional investors to achieve in a
on where to deploy capital, what level of risk to take, and how
short period of time given that the average loan size is just north
to diversify their portfolios. Originators make judgments about
of $11K. Orchard quantitative research has shown that a portfolio
the future when they develop new products, invest in customer
of at least 200 loans is fairly well diversified. Of course, this type
150%150% 150%150%
150%150% 150%150%
acquisition, and calibrate their underwriting criteria to approve
of diversification mainly protects an investor from variance in
or decline borrowers. While it is impossible to predict exactly
borrower credit risk, limiting the impact of a small number of
125%125% 125%125%
what the future will bring, we know that good times do not
loans on the investor’s overall return. In order to solve for other
100%100% 100%100%
last indefinitely, and it is prudent to discuss what marketplace
forms of risk, investors may wish to diversify in other ways as well.
participants might do to mitigate risk in the event of market stress.
125%125% 125%125% 100%100% 100%100% 75% 75% 75% 75% Jan ‘14 Jan ‘14 Jul ‘14Jul ‘14 Jan ‘15 Jan ‘15 Jul ‘15Jul ‘15 Jan ‘15 Jan ‘15 Jul ‘15Jul ‘15 Jan ‘14 Jul ‘14Jul ‘14 Jan ‘15 Jul ‘15Jul ‘15 Jan ‘15 Jul ‘15Jul ‘15 Jan ‘14 Jan ‘15 Jan ‘15 Date Date Date Date
15
Orchard Platform
Portfolio Portfolio Value Value
175%175% 175%175% Portfolio Value Portfolio Value
175%175% 175%175% Portfolio Portfolio Value Value
Portfolio Value Portfolio Value
2014 - 2015
Portfolio Portfolio Value Value
175%175% 175%175% Portfolio Value Portfolio Value
175%175% 175%175% Portfolio Portfolio Value Value
Portfolio Value Portfolio Value
TICKERS TICKERS AGG: iShares AGG: iShares Barclays Barclays Agg. Bond Agg.Fund Bond FundHYG: iShares HYG: iShares High Yield HighCorp YieldBond CorpETF Bond ETFOrchard Orchard Consumer Consumer LendingLending Index IndexSPY: SPDR SPY:S&P SPDR 500 S&P Trust 500ETF Trust ETF TICKERS TICKERS AGG: iShares AGG: iShares Barclays Barclays Agg. Bond Agg.Fund Bond FundHYG: iShares HYG: iShares High Yield HighCorp YieldBond CorpETF Bond 2013 ETFOrchard Orchard Consumer Consumer LendingLending Index IndexSPY: SPDR SPY:S&P SPDR 500 S&P Trust 500ETF Trust ETF 2012 - 2015 - 2015
Management Of Risk In Anticipation Of Stress
Throughout this paper, we have employed a scenario-based approach to stress testing. Rather than predicting the future, we attempt to understand the impact that various versions of a possible future would have on a marketplace lending portfolio. Indeed, attempting to predict the future can be seen as a fool’s errand: It’s impossible to be perfectly right; the question is the magnitude of difference between prediction and reality.
75% 75% 75% 75% Jan ‘15 Jan ‘15 Apr ‘15 Apr ‘15 Jul ‘15Jul ‘15 Oct ‘15 Oct ‘15 Jan ‘15 Apr ‘15 Apr ‘15 Jul ‘15Jul ‘15 Oct ‘15 Oct ‘15 Jan ‘15 Date Date Date Date
As in other asset classes, diversification is a vital component of any risk-mitigation approach. The primary way to diversify is to spread investments across a sufficiently large number of loans,
Stress Testing
16
MANAGEMENT OF RISK IN ANTICIPATION OF STRESS
Another key area of risk is that of the originator and servicer,
standards have been developed to handle cross-border transactions,
securitization, representing approximately $8B of transactions
often the same entity. While the leading originators in marketplace
and withholding-tax regimes make overseas investing unattractive in
over the past two years. While these deals are generally seen as a
New
lending have posted track records of high-quality underwriting
some jurisdictions.
positive development for the market and a beneficial component
Guard
and servicing, there are still risks to consider, such as originator
of investors’ financing strategy, they also have drawbacks,
bankruptcy, fraud, or technical failure. The practice of designating
Finally, diversification can also mean the inclusion of marketplace
including a size, cost, and complexity that make them available
a backup servicer is widespread and now considered essential,
loans as one asset in a broader portfolio. Even if conditions are
to only the largest of managers. A more nimble and transparent
but to date there has not been a major failure event that would
predicted to worsen, it may be difficult to get the timing of the
market for these loans would increase liquidity for a variety of
test the ability of a backup servicer to step in and take over from
deterioration right. If performance deteriorates more slowly than
asset owners.
the primary servicer. Even in a relatively seamless transition,
expected, there is an opportunity cost from not holding marketplace
there would likely be some disruption to borrower payments
loans in a portfolio. Furthermore, as a short-duration asset, if
Planning for a stressed environment and mitigating the risk of a
and cash flows to investors. Investors who diversify their market
performance deteriorates beyond what is expected, an investor can
downturn is not a task for investors alone. Indeed, the originators
participation across multiple originators—particularly among
recover principal through normal amortization, even in the absence
have a strong role to play in creating and nurturing a stable
those of different asset classes, borrower types, and loan product
of immediate liquidity.
financial ecosystem and a strong incentive to pursue responsible
durations—will be in a stronger position and less vulnerable to originator-related volatility.
DEVELOPING A ROBUST SET OF NEW ACCOUNT CRITERIA ALONG WITH A PREDICTIVE AND STABLE CREDIT RISK MODEL TO BE USED IN UNDERWRITING ARE THE MOST IMPORTANT THINGS AN ORIGINATOR NEEDS TO DO. In addition to investing in a large number of loans across multiple originators, investors can also diversify by spreading their exposure to macroeconomic factors. This could include investing in heterogeneous geographic areas, which would likely respond differently to trends in employment levels or home prices. Investing across geographic areas could involve spreading capital across multiple countries and currencies, though this has been quite difficult in marketplace lending thus far. No real international
growth. A core part of any originator’s business is deciding Some investors may wish to mitigate their marketplace lending
which customers to approve for loans. Developing a robust set of
exposure through hedging—executing transactions in other
new account criteria along with a predictive and stable credit risk
assets whose performance would be orthogonal to that of the
model to be used in underwriting are the most important things
marketplace portfolio. However, unlike in more mature asset
an originator needs to do. In this area, marketplace lenders
classes, there are neither out-of-the-box products nor the market
are in an interesting position relative to their more established
mechanics or legal framework to provide a true hedge. For
counterparts in the banking world, in terms of both challenge
instance, there is no way to “short” a marketplace asset, and there
and opportunity.
are no widely-available credit default swaps or similar derivatives
Traditional vs. New Guard in Times of Stress
Historical Data
•
Advantage: Traditional
Lending is not a new business, and experienced lenders have many years worth of data across multiple credit cycles.
Experience
•
Advantage: Traditional
Experience in multiple economic environments is valuable in times of stress.
System Flexibility
Advantage: New Guard
•
Systems built recently with flexible and modern technology are more easily modified and can handle a greater breadth of risk models and dataintensive strategies. Legacy systems at traditional financial institutions often slow a lender’s ability to adapt to changing conditions.
Data Science
Advantage: New Guard
•
Newer online lenders generally have the
that would pay off in a default scenario. Some investors in today’s
As marketplace lenders contemplate how to develop strategies
market have employed relatively primitive hedging strategies,
that will perform in a variety of environments, risk managers
sources along with novel modeling software and
such as trading in assets that track the performance of consumer
will benefit from conducting what is known as “through-the-
techniques, without the red tape of corporate
credit in general, or trading in currency swaps depending on the
cycle” risk modeling. Any modeling activity requires a set
purchasing bureaucracy and legacy technology.
currency in which their assets are owned. As the market grows and
of assumptions, and these should be constructed with the
matures, more specific and sophisticated hedges will likely emerge.
expectation that economic cycles will fluctuate. So, to provide
Human Capital
flexibility to use a variety of alternative data
Advantage: Uncertain
a fairly simple example, a lender issuing a 5-year term loan
In a stressed environment, traditional and
Of course, in any market with any form of uncertainty, the best
might assume that some of those years will take place in a
alternative lenders will likely use their human
protection is offered by liquidity. A liquid market makes it possible
good economy while others will take place in a bad economy,
for investors to unwind their positions if needed, to execute
ideally constructing models and strategies that can yield good
more nuanced transactions as a hedge against risk, and to obtain
performance through a varied economic cycle.
timely and updated pricing data for their assets based on market
Traditional
~
~
capital in different ways. Lenders with a long track record have employees with experience in handling different economic scenarios and processes for scaling human-driven collections activity up and down as needed. On the other
demand and transaction history. To date, several large holders
hand, alternative lenders may be able to make
of marketplace lending assets have obtained liquidity through
people-related changes more quickly in a downturn without the overhead of corporate bureaucracy and hindsight bias.
17
Orchard Platform
Stress Testing
18
MANAGEMENT OF RISK IN ANTICIPATION OF STRESS
CONCLUSION
In a stressed environment, lenders will also want to closely monitor
borrower’s deposit account. With such a frequent payment cycle,
their application volume, mix, and quality from various origination
lenders can more immediately identify borrowers in financial
channels, as these characteristics can change quickly. Inevitably,
distress and take action to ameliorate the situation.
certain heavily stressed lenders will pull out of or adjust their spend in a given channel, which may change the dynamics of the channel’s
In a challenging economy, consumer and business borrowers
applicant pool. In such a circumstance, originators relying on that
will inevitably face financial stress, which will impact their ability
channel for borrower acquisition will do well to monitor closely for
to make scheduled payments on their debt obligations. Even
negative selection bias or for an applicant mix that does not meet
with the best underwriting criteria and most thoughtful through-
the expectations they had when they began solicitation through that
the-cycle planning, originators will need to deal with a greater
channel. In the Great Recession of 2008–2009, this challenge was
potential for delinquencies and losses. This involves having the
felt acutely by credit card issuers who sourced applicants through
infrastructure, partnerships, and plans in place to rapidly scale
third-party affiliate websites. As some card issuers drastically
up servicing and collections capabilities when necessary. Smart
reduced their marketing expenditure or even shut down entirely,
originators will also pay close attention to customer experience
those remaining in the online channel faced a very different and
to ensure that it is not negatively affected by more-aggressive
potentially higher-risk applicant mix. Making both marketing spend and underwriting criteria channel-specific can help an originator to be more resilient in a changing environment.
As we’ve mentioned, the purpose of this discourse is not to try to
possible that they could be strategically subordinated to other debt
predict the future but rather to attempt to understand the impact
obligations that carry more significant or immediate consequences.
that various versions of the future would have on a marketplace
These types of aforementioned intangibles require additional
lending portfolio and offer our guidance. Our analysis, based on
deliberation and are more a matter of behavioral economics than
the critical assumptions we have made and the stress framework
rigorous data analysis. Planning for a stressed environment and
servicing and customer management.
we have defined, yields qualitative and quantitative conclusions
mitigating the risk of a downturn is not a task for investors and
about expected marketplace lending performance during a
originators alone, but a requirement for all industry participants.
For originators, just as for investors, liquidity is king. In order to
hypothetical challenged economic scenario.
continue lending to borrowers, an originator must have consistent
Of course, underwriting does not end with the approval and
access to capital. Given that the providers of capital—investors,
booking of a new loan. Successful lenders manage risk closely
banks, and the like—will be subject to many of the same economic
throughout the customer lifecycle. The levers available for customer
forces in a changing market, originators with many diverse sources
management vary with the type of loan product. For revolving
of capital will be better prepared to weather the storm without
products such as credit cards, lenders can increase or reduce the
facing liquidity challenges. During the Great Recession, certain
borrower’s credit limit at any time in response to account activity
funding channels dried up, and some lenders went out of business
or a changed assessment of the borrower’s risk. On term-loan
or were forced to sell because they could not raise enough new
products, lenders don’t have the same flexibility, but they have
funding to fulfill already-existing debt obligations. In good times,
other options, such as proactively adjusting the repayment term of
the securitization markets and bank warehouse facilities are useful
a borrower’s loan based on identification of financial stress. Any
and attractive options. However, markets open and close, spreads
customer-management strategy depends on the lender’s ability to
widen, and banks can pull their credit lines. As a result, access to a
continuously monitor both the status of the loan and the borrower’s
diverse marketplace of institutional capital is particularly valuable
credit. Lenders can pull updated credit bureau data on a periodic
for originators. If originators have the ability to fund loans using
basis to identify deterioration, and some credit bureaus offer
capital from a variety of investors, they will be less dependent on a
trigger-based systems that raise an alert if a certain action takes
single source.
place on a customer’s credit file. One innovation that is particularly helpful to some alternative lenders is that of the daily-pay credit product. Certain issuers offer products that pay down the loan by debiting a small amount each day, rather than each month, from the
19
Orchard Platform
Conclusion Perhaps the biggest takeaway relates not to the challenges that Our forecasts, using the data available to us and leveraging
would face marketplace lending, but rather to the opportunity
our team’s credit expertise, suggest that marketplace lending
that such economic uncertainty would present to the industry as a
should prove remarkably durable to various economic stressors.
whole. While every originator’s underwriting model looks flawless
Understandably, yields would be lower, but our sensitivity analysis
in a good economy, what happens when things start moving
indicates that it would require significant levels of stress in order
sideways? This would be marketplace lending’s “Darwinian”
for a thoughtfully constructed marketplace lending portfolio to
moment: Are the innovative underwriting models employed by
realize negative returns. As an asset class, marketplace lending has
marketplace lending upstarts capable of better managing risk
some clear advantages, including lower volatility and a greater
than their legacy counterparts? Is the ability of leading platforms
degree of flexibility. However, there are also some areas that
to leverage proprietary technology and large amounts of data
suggest cause for concern, and these should be closely monitored
adaptable to changing market conditions? With the world
and managed going forward. For example, the quality and
watching and naysayers expecting failure, a resilient performance
efficacy of backup servicing models in the event of originator
by marketplace lending in the face of significant adversity has
bankruptcy is untested. While originators and investors are
the potential to cement the current shift in credit and catalyze
paying an increasing amount of attention to this issue, no level of
continued growth and prosperity.
analysis can simulate these types of untested systems and capacity challenges. As Mike Tyson famously said, “Everyone has a plan ’till they get punched in the mouth.” A similar concern is where marketplace debt obligations would register on the payment hierarchy for a borrower faced with financial stress, and it’s
Stress Testing
20
ABOUT THE AUTHORS
David Snitkof
Larry Haertel Jr.
Raymond Han
Michael Toth
CHIEF ANALYTICS OFFICER
SENIOR MARKETING MANAGER
PLATFORM DATA ANALYST
MANAGER, INVESTMENT AND
AND CO-FOUNDER
CREDIT STRATEGY
David Snitkof has applied analytics and technology to banking,
Larry manages Orchard’s product marketing efforts, working closely
Raymond started his career at a high-frequency trading shop in Chicago
Michael Toth has four years of experience working in credit risk
healthcare, travel, and media for over ten years. At American Express,
with the product and sales teams to develop Orchard’s positioning and
as a quantitative trader/programmer. While there, he made markets in
analytics. Prior to joining Orchard, Michael was an associate at
he worked on risk, product, and marketing analytics for new consumer
help bring new products to market. Larry is also a regular contributor
futures options and performed analyses on the firm’s pricing strategies.
BlackRock. He was responsible for the valuation and risk analysis of
card products and partnerships and also developed the underwriting
of content to the Orchard blog and serves as in-house editor for
Afterwards he joined Morgan Stanley as a trading desk strategist in
mortgage whole loans and securitized products for several financial
criteria used to approve or decline billions of dollars in new credit.
external content initiatives. Larry first joined Orchard as an intern while
the securitized products group where he focused on bonds backed by
institution clients, covering portfolios with valuations in excess of $400
At Citigroup, David led a team driving analytics and strategy for the
completing his MBA at UCLA Anderson and came on full time upon
consumer debt such as student loans, credit cards and auto loans as well
billion. Michael is a graduate of the Wharton School at the University
full Small Business credit lifecycle. David also was head of analytics
graduating and moving back to New York. Prior to getting his graduate
as esoteric finance. Raymond’s responsibilities included knowing the ins
of Pennsylvania, where he received a B.S. in Economics with Finance
and marketing at Oyster.com, an online travel startup since acquired
degree, Larry held sales roles at UBS and Curbed and also gained valuable
and outs of different bond structures and the credit of the underlying
and Statistics concentrations. In his free time, he enjoys traveling,
by TripAdvisor. David excels at developing creative uses for data,
marketing analytics experience as an intern at ChowNow. A graduate of
collateral. He has also built reports which helped the desk manage
playing chess, and programming.
communication of technical concepts, and building high-performing
Brown University, Larry won the Ivy League Championship while also
risk positions. Raymond is an alumnus of Brown University where he
teams and products. He graduated from Brown University, where he
earning three-time All Ivy League honors as captain of the golf team. He
studied applied math and computer science.
studied Economics, Cognitive Psychology, and Neuroscience.
remains active on the local and national competitive amateur golf circuit.
[email protected]
[email protected]
Orchard is the leading provider of technology and data to the marketplace lending industry, powering the interaction between institutional investors and loan originators. Founded in New York City in 2013, Orchard’s orchardplatform.com
mission is to build the systems and standardize the data that will allow marketplace lending to efficiently grow into a global financial market. Orchard provides products and services to investors that enable them to understand, access, and execute marketplace lending investments, including Market Data & Research, a powerful Order Management System, and detailed Reporting & Analytics. Orchard offers originators access
Orchard Platform
[email protected]
DISCLAIMERS © 2016 Orchard Platform Advisors, LLC. All rights reserved. This paper is provided by Orchard for informational purposes only. Actual loan or business performance may differ significantly from historical performance or market data. Estimates and projections are based upon data provided by recipient and/or other sources that we deem to be reliable but we do not guarantee that such sources are complete, accurate, or free of errors or omissions. Any conclusions or estimates presented herein may become
in loans and related financial products should be financially sophisticated and prepared for significant losses. Investors may or may not be able to invest in loans that meet their desired characteristics. Loans are also subject to certain legal and regulatory risks that may render them unenforceable. Any graph, chart, formula, or other device represented or described herein should not be used exclusively and must be interpreted by an experienced and sophisticated investor in order to effectively assist in any investment decision. These materials are not an offer to sell, nor a solicitation of an offer to buy, any securities.
to a diverse group of institutional investors who use Orchard to purchase marketplace lending assets. A single
inaccurate over time. Orchard has no obligation to update any of the statements or analysis
integration using Orchard’s proprietary approach to data standardization enables end-to-end marketplace
presented. These materials are provided "as is" and without guarantees, assurances, or
Orchard Platform Advisors, LLC is an SEC registered investment adviser headquartered
warranties of any kind, express or implied. Orchard does not provide and these materials do
in New York, NY. Orchard does not provide legal advice, tax advice, or accounting advice.
support covering Investor Awareness, data-driven Market Insights and seamless Data Management. Orchard
not constitute legal advice, tax advice, or accounting advice.
Before making any investment or executing any transaction, you should consult with your
has been named to Forbes Next Billion Dollar Startups list, produces the Orchard US Consumer Marketplace
Loan purchases and similar transactions give rise to substantial risk and may not be suitable
Lending Index — the only industry wide benchmark distributed on the Bloomberg Professional service — and
that loans purchased will perform in line with historical loans, or that specific loan categories
These materials are proprietary and confidential and may not be copied, distributed, or
will be available or suitable for purchase by particular investors. Loans can and do default,
shared with any third party without the prior written consent of Orchard.
is recognized for its technical and analytical thought leadership as explored on its blog.
21
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for all investors. No assurance can be made regarding the future performance of any loan,
legal, tax, and accounting advisors with respect to the suitability, value, and risk of such investment or transaction.
which may result in significant losses, including the loss of all principal invested. Investors
Stress Testing
22
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