Mac's Office of the Chief Economist takes an intensive look at marketplace
lending in the December issue of its Insights
and Outlook. A marketplace lender
(ML) is a non-bank intermediary that provides one or more types of consumer
loans, usually on line. Some but not all
rely on peer to peer lending (shorthanded as P2P lending by Freddie Mac) and
some concentrate on niches such as debt consolidation loans or small business
lending. Some of the more well-known
examples are Prosper, a peer to peer lender, and Lending Club, the first ML to
announce an initial public stock offering.
borrowers served by MLs often have limited credit histories that make it
difficult to tap into traditional lending sources and most loans are unsecured. However some MLs are now doing auto loans and
some mortgage lending and others have announced their intention to enter the
Mac says it is difficult to determine the direction of marketplace lending. They could be offering a technical advance
through underwriting methods to reach market segments not served by traditional
lenders or merely attempting to circumvent regulation. Is peer-to-peer lending a new form of "financial
intermediation" or just a temporary stepping stone to a traditional lending structure? "Will marketplace
lenders become an Uber-like disruptive force in consumer lending, or are they simply
old-fashioned consumer lending dressed
up for the Internet?" Finally Freddie asks if MLs can move beyond
unsecured consumer lending and become mortgage lenders.
While ML is a new phenomenon
it is growing rapidly and the different business models mean there is no
typical one. Freddie Mac looked at some of their notable characteristics.
can function somewhat similarly to a typical bank, taking money from investors
and lending it to consumers. Others,
probably most at this point, act as matchmakers, allowing investors to choose
individuals and business to which they want to lend.
lending first appeared in the United Kingdom in 2005 and in the U.S. the next
year. Morgan Stanley estimates that this
lending, while still small, was on track to make originations totaling around
$15 billion this year and volume is growing rapidly.
in traditional bank operations, P2P doesn't have depositors but instead
utilizes the money of investors. Also
unlike a traditional bank where depositors' money is protected by bank
insurance and those depositors don't have to be concerned about credit
worthiness and often have no idea of the types of loans the bank is making, in P2P
lending the risk goes to the investor.
ML matches investors to individual loans and investors can buy into them in
small amounts - as little as $25 - and thus can diversify their risk. Some MLs
are set up so investors and borrowers have common ties - for example being
alumni of the same school. In addition
to serving as matchmaker between investor and borrower the ML underwrites the loan
and services it, collecting a transaction and servicing fees from both sides of
the transaction. This business model
allows MLs to operate with small balance sheets and low capital ratios. Freddie Mac points
out that other types of institutions share some of the P2P characteristics such
as providing opportunities for individuals to invest in second mortgages and
small business loans through brokers or the common ties held by members of
mutual or cooperative institutions such as credit unions.
lending is actually more complicated than the above description implies. Sometimes the MLs need funding to cover a
loan between its close and sale to investors and may obtain warehouse funding
from banks to cover the gap. Others may not fund a loan until it is fully
committed to by investors.
Not all MLs are P2P lenders,
some partner with banks or other institutional investors and operate in a
fashion similar to mortgage
brokers. Some of the larger MLs have begun to securitize loans, tapping the private
placement or capital markets for funds. It may be that more-successful MLs will outgrow
the P2P method
of funding loans
Not unlike traditional banks MLs make
heavy use of the Internet but their use is distinguished from that of
traditional banks by two characteristics - they tend to emphasize social media
elements and advertise online underwriting models
that incorporate nontraditional criteria.
Freddie Mac points to the ML SoFi, its very name a contraction of social
and financial. Its website refers to its
borrowers as "members," offers a "Partner" program for firms that employ or have
business relationship with current or potential SoFi members and its pages
provide links to others describing "member stories",
career planning and job search
assistance services, an Entrepreneur program (mentorship, access to investors,
loan deferrals), a referral
program, and events
like happy hours, community dinners, and career seminars.
In the second instance,
while underwriting models are proprietary some MLs that specialize in student
loan consolidation target borrowers who have short credit histories but instead
take into account factors like SAT scores, schools attended, and current
jobs. Some MLs specialize in lending to
a narrowly defined group of borrowers such as graduates of a particular school
or type of school, others concentrate on types of loans such as debt
Freddie Mac says while it is
hard to document it appears the Millennials are the dominant ML borrowers and
some survey evidence that they have high awareness of it and are comfortable
with the on-line application process.
The types of loans offered, such as student loan refinances and the
relatively small loan sizes may appeal to younger consumers as well.
While ML are not subject to
banking regulation or examination they must conform to some state and federal consumer
and licensing laws and examination by the Consumer Financial Protection Bureau
(CFPB). After sanctioning Prosper for
violations of the Securities Act in 2008 the Securities and Exchange Commission
now treats all P2P lending transactions as sales of securities and requires all platforms to register
With respect to the growth of this market, PricewaterhouseCoopers LLP estimates the market could reach $150 billion by
2025 while others put a much higher number on it. ML could present a disruptive innovation that
threatens traditional lenders but others question these forecasts as the
industry is still comprised of relatively small firms with limited capital.
This industry has not yet
been through a shake out, leaving questions about its resilience. Larger banks
could always adopt some of the industries more appealing features or simply buy
out the most successful firms. "It's too soon to tell whether
marketplace lending is the next Uber or just another
flash in the pan,"
Freddie Mac says, and suggestions some of the factors that could decide the
Cost reduction. By operating
as nonbanks and avoiding balance
sheet lending, MLs have gained
a significant cost advantage
and traditional lenders may be pushed to adopt some aspects of the ML model to
Niche lending. By virtue of their small size and lower costs, MLs can target niche markets which larger lenders may not find profitable
Nontraditional underwriting. MLs advertise proprietary
algorithms that outperform industry-standard credit scores, especially for
borrowers with limited credit histories.
These have yet to be tested in a "challenging economic environment."
They may fail or they may make a significant technical breakthrough.
Mortgage lending. MLs have focused largely on unsecured consumer
lending followed by small business loans and student debt refinances with only
small ventures into secured lending to date.
One barrier to change is the complexity of mortgage lending compared to unsecured lending
Regulatory evolution. Regulators may increase oversight of MLs,
particularly if it continues such a high growth rate. Its underwriting algorithms may raise
questions about both prudential and fair lending and the practice of funneling loans
through banks - the
so-called "rent-a-charter" relationships, may raise questions about attempts to evade regulation.
Mac concludes by saying that the current crop of MLs could fail in the next
downturn, regulators could take a stronger interest, or the cost advantages of
ML may not extend to mortgage lending, but innovation is difficult to stop. New
companies will find new ways to improve business models, large banks may adopt
ML innovations but no matter what, "expect change."