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Future of Finance Is P2P as LendingClub Goes Public with $5.4B Valuation

Future of Finance Is P2P as LendingClub Goes Public with $5.4B Valuation | Orchard P2P Lending | Scoop.it
Future of Finance is P2P as LendingClub Goes Public with $5.4B Valuation
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Research: P2P Lending Goes to £40 Billion in 2016

Research: P2P Lending Goes to £40 Billion in 2016 | Orchard P2P Lending | Scoop.it
Research and Markets have announced a new report they have published on the fast growing peer to peer (P2P) lending industry. Their numbers state the glob
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With Karrot, Kabbage Digs Into Lending Club’s And Prosper’s Consumer Loans Business

With Karrot, Kabbage Digs Into Lending Club’s And Prosper’s Consumer Loans Business | Orchard P2P Lending | Scoop.it
“ Kabbage, the Atlanta-based startup that has raised hundreds of millions of dollars to build and run a money lending platform for small, online businesses, is..”
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A Closer Look at Debt Consolidation Loans

As any follower of the marketplace lending space knows, the primary use
case for consumer borrowers today is debt consolidation – presumably
revolving credit card debt that generally carries punitively high interest
rates.   Based on data from the Federal Reserve, these rates average 13%
but can be much higher.
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Research: P2P Lending Should Focus on Partners, New Opportunities and

Research: P2P Lending Should Focus on Partners, New Opportunities and | Orchard P2P Lending | Scoop.it
Research: P2P Lending Should Focus on Partners, New Opportunities and ...
Crowdfund Insider
A recent study published by Cognizant addressing the fast growing peer to peer lending space in the United States.
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P2P Digital Banks Are Lending Billions of Dollars with 2 companies owning 98% of the market

P2P Digital Banks Are Lending Billions of Dollars with 2 companies owning 98% of the market | Orchard P2P Lending | Scoop.it
Adweek
Peer-to-Peer Digital Banks Are Lending Billions of Dollars
Adweek
A recent Fitch Ratings report shows that the peer-to-peer (P2P) digital banking space has become a billion-dollar industry and is growing fast.
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P2P Lending Sites: An Exhaustive Review

P2P Lending Sites: An Exhaustive Review | Orchard P2P Lending | Scoop.it
A complete list of every peer to peer lending site in North America. (P2P Lending Sites: An Exhaustive Review: http://t.co/8bpZ3MQtaP)
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International P2P Lending Services – Loan Volumes July 2014

International P2P Lending Services – Loan Volumes July 2014 | Orchard P2P Lending | Scoop.it
RT @p2plender: RT @wiseclerk International P2P Lending Services – Loan Volumes July 2014 http://t.co/lzDTUp4g3S #p2p-lending
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LendingClub vs. Prosper – Which is the Better Option for P2P Lending and Investing?

A Blast From the MPFJ Archives! - : LendingClub vs. Prosper - Which is the Better Option for P2P Lending and... http://t.co/TCtY3bflV3
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Top 5 Peer to Peer Lending Sites

Top 5 Peer to Peer Lending Sites | Orchard P2P Lending | Scoop.it
1. Lending Club

Lending Club was founded in 2007 and is the largest peer-to-peer (p2p) lending platform in the US. “Fueled by the value we deliver, Lending Club has consistently grown ...
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Lending Club: One Billion Dollar Quarter (Infographic)

Lending Club: One Billion Dollar Quarter (Infographic) | Orchard P2P Lending | Scoop.it
Peer to peer (P2P) lending platform Lending Club is having a pretty good year.
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Therese Torris's curator insight, July 10, 2014 9:50 AM
Over 288,000 loans to refinance credit cards or a different loanLowered credit card interest rates an average of 29%Historical returns for investors range from approximately 5% to 8%
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What the Lending Club IPO Will Mean for Investors - Lend Academy

What the Lending Club IPO Will Mean for Investors - Lend Academy | Orchard P2P Lending | Scoop.it
Four Benefits for P2P Investors. But in this article I want to ... in all 50 states. This does not happen automatically so it will not change overnight but shortly after the IPO Lending Club should be open to investors in every state.
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Barbarians at the gate? Or the making of an industry?

Barbarians at the gate? Or the making of an industry? | Orchard P2P Lending | Scoop.it
The dam has given way and the large institutions have arrived in UK peer-to-peer (P2P) lending.Earlier this month – amidst.
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Wharton Education Series: P2P Lending

Wharton Education Series: P2P Lending | Orchard P2P Lending | Scoop.it
Visit the post for more.
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The Orchard Lendscape

The Orchard Lendscape | Orchard P2P Lending | Scoop.it
“Marketplace lending is a growing and increasingly complex ecosystem. Making sense of all the various players and the ways they connect can be a challenge. To help, Orchard Platform has created a “Lendscape” that brings the industry into focus.”
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International P2P Lending Services - Loan Volumes August 2014

International P2P Lending Services - Loan Volumes August 2014 | Orchard P2P Lending | Scoop.it
International P2P Lending Services - Loan Volumes August 2014
P2P-Banking.com
In August Prosper, Bondora and Thincats showed big growth of newly originated loan volume. For most other services it was a slow month.
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The Fitch P2P Lending Report: 5 Things They Got Right and 3 Things They Got Wrong

The Fitch P2P Lending Report: 5 Things They Got Right and 3 Things They Got Wrong | Orchard P2P Lending | Scoop.it
The Fitch ratings agency, who along with Standard & Poor's are the 2 largest US based ratings agencies just released their first report on Peer to Peer Lending.
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P2P Lending Is Poised to Grow :: Federal Reserve Bank of Cleveland

#P2P growing 84% per quarter @clevelandfed Peer-to-Peer Lending Is Poised to Grow Federal Reserve Bank of Cleveland http://t.co/PCczhlBJc7
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P2P Lending – a Funding Channel Set to Grow

P2P Lending – a Funding Channel Set to Grow | Orchard P2P Lending | Scoop.it
Cleveland FED: Peer-to-Peer Lending – a Funding Channel Set to Grow Forex Magnates With the business originating in the UK back in 2005, US companies which provide P2P business lending have been limited to providing up to $100,000, with Lending...
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Peer-to-Peer Lending Is Poised to Grow

RT @ClevelandFed: Peer-to-peer lending is poised to grow #P2P http://t.co/kylMEVyKh6
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Revisiting Roll Rates using Markov Chains

Revisiting Roll Rates using Markov Chains | Orchard P2P Lending | Scoop.it
In October of 2013, we did a post on Roll Rates for Lending Club.  We
defined roll rates and analyzed the patterns on Lending Club data.   For
the purposes of both posts, we’ll consider roll rates to be the probability
of a loan going from one state of delinquency to another (e.g. 30 days past
due to charge off).  Roll rates provide insight into the likelihood of
future loss on a loan that has missed just one payment.  This can be used
for:

1. Modeling: it is best practice to use more recent data as the current
vintages are underwritten and aging during a similar period of time.  To
actually charge off, an account needs at minimum 120 days (although – it
usually takes at least 10 months or so.)  If you can use an early default
predictor like missing 1 payment (i.e. 30 days past due) you can adjust the
model with this information. 

2. Portfolio Analysis: If you know the roll rates of a population, you can
then extrapolate the current performance of your portfolio earlier because
you can use early indications as proxy for later credit loss.  This allows
for adjustments in underwriting strategy prior to actually experiencing
losses.

3. Loan Loss Reserve Calculations: If an investor keeps a reserve based on
expected losses, roll rate calculations can be useful. 

In order to calculate roll rates, it is important to first understand the
nature of charge-offs, as the analysis requires some assumptions.  These
loans amortize over time, which means if the charge off occurs later in the
borrower’s tenure, the principal charged off could become de minimis. 
Below is the average dollar loss and percentage of original principal lost
based on when the charge-off occurs in the life of the loan.  As expected,
the average dollars lost decreases as the loans age, as does the percentage
of the original balance that charges off.

As opposed to Lending Club (which only designates past due loans as 31-120
days late), Prosper’s data allows for a more granular assessment of the
transitions between the different past due buckets.  Prosper provides the
actual days past due of every loan at every month.  In order to calculate
loan movement, we need to pick a starting point.  Based on the distribution
of 30 days past due (below), 50% of loans that miss one payment do so by
month 12, so this will be the starting point.

We analyzed all Prosper loans that have at least 18 months tenure to see
the actual change in status from 12 months to 18 months.  We used a
statistical method called Markov Chains, also known as transition matrices.
 These are mathematical models that calculate the probability of an object
moving from one state to another.  In this case, the states are the status
of the loan, and the time period we are analyzing is 6 months (from 12 to
18 months).  By applying this model to the historical changes in loan
status, we are able to extrapolate the likelihood of a loan in any status
moving to another status in 6 month increments from the initial 12 month
status.  

Below are the results of the analysis, in which we show the probability of
movement between all of the different status buckets.  The likelihood of
eventual charge-off on loans that miss just one payment by 12 months is
quite high.  When predicting out to 30 months, our analysis shows the
likelihood to be about 85%.

The Markov Chain is a useful tool, and was easy to use for this analysis.
 In the case of roll rates, this analysis could be accomplished with any
starting point and ending point.  In this case, we used 12 months to start
and looked out 6 months.  If an analysis required even more recent data,
then starting at 3 months and looking to 6 would work.  Making this change
to the analysis would bring in more recent data (including all loans with
at least 6 months of tenure, instead of 18), but the tradeoff would be a
model that may under predict the probability of charge off because it goes
out to 9 months instead of 18 months.

Using statistical methods, both basic and complex, can help yield
preliminary results for a loan portfolio.  This analysis specifically helps
validate the use of early default behavior as an input into a charge-off
model.  Based on what we've found, an analysis done on a more recent
vintage can yield results that are worthwhile.  Of course, more data is
always better, and actual performance is always the optimal input to a
model.  In the case where this is not available, statistical methods such
as those discussed here are useful.
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Repeat Borrowers – Relationship Lending for the Modern Age

Repeat Borrowers – Relationship Lending for the Modern Age | Orchard P2P Lending | Scoop.it
Assuming that marketplace lending offers borrowers a good deal and a
positive customer experience, we would expect to see repeat business.  In a
post last October, we first analyzed repeat borrowers on Prosper.  That
analysis found that 10% of loans were issued to those who had previously
taken out a Prosper loan.  In Oct. 2013, Prosper originated $50 million in
loans. Since then, Prosper has issued an additional $726 million, including
$145 million in June 2014 alone.   Given the massive growth in the
marketplace, we wanted to see how much of this growth was due to repeat
borrowers, how these individuals have performed, and what we can learn from
borrowers’ prior experience.

Prior Borrower Market Share

The charts below show monthly loan originations on Prosper as well as the
share comprised by repeat borrowers.

As we can see, Prosper’s origination volume has grown significantly over
the past 8 months.  Existing borrowers, while growing in absolute number,
have comprised a smaller share of monthly issued loans over time.  This
pattern is not surprising given the platform’s high rate of growth.  In
order for Prosper to expand, it has presumably needed to cast a broader net
in acquisition marketing to source borrowers from new channels.

When Borrowers Return

In the first half of 2014, Prosper made 3,455 loans to previous borrowers,
totaling $40,185,826 in originations.  Using the data made available by
Prosper, we can explore the characteristics of this population.  In the
chart below, we group these borrowers by the number of previous loans they
had taken prior to the new loan’s date of origination.   While the vast
majority had taken only 1 prior loan, 35% had 2 or greater!

For the borrowers with one prior loan, one has to wonder how much time had
passed between the issuance of the prior loan and the new one.  In the
histogram below, we  show the distribution of time between loans, divided
into 3-month intervals and broken out by the term of the previous loan.

Interestingly, a very large proportion of new loans were granted to
borrowers who had already received Prosper loans under a year ago.  The
vast majority of repeat loans were granted within 2 years of the prior
origination, perhaps a surprising finding given that Prosper’s minimum loan
term is now 3 years (a small number of 1-year loans were issued in the
past, but this practice stopped in early 2013).   If so many borrowers are
getting new loans prior to the initial maturity date of an existing loan on
the same platform, there are various potential reasons to consider.

1. The borrower is current on the existing loan and has sufficiently
good credit to qualify for an additional loan (potentially to
refinance the first one)
2. The borrower has paid off the existing loan and now qualifies for an
additional loan
3. The borrower defaulted on  the existing loan (note – this scenario
would not occur within Prosper’s underwriting policy, as prior
defaulters are  restricted from obtaining new credit)

Understanding the frequency and details of the above scenarios is an
analysis unto itself and perhaps will be the subject of a future post.

Creditworthiness of Prior Borrowers

Presumably, if Prosper has decided to give an additional loan to a prior
borrower, its own credit rating system has favorably evaluated this
individual.  Therefore, to get an externally consistent view of the
creditworthiness of repeat vs. first-time borrowers, we must use an
externally-developed model: in this case, FICO.  In the graph below, we
show the distribution of loans by FICO score, split out by the number of
prior Prosper loans at the time of origination.  The graph  reveals a
relatively stable distribution between new and prior borrowers, with some
rightward-skew for those with a previous loan.  Perhaps the higher scores
for these individuals reflect good performance on the earlier loan.

Conclusion – Relationship Lending

The concept of “relationship banking” has existed for decades in
traditional financial services.  The idea was that customers who were
already doing business with a given institution would prefer to come back
to that same institution as repeat customers and for additional services. 
Embedded in this concept was the assumption that this would allow a bank to
make more accurate credit decisions, aided by a wealth of information on
existing customers and the ability to consider a customer’s lifetime
value.  With this idea in mind, retail banks across the country expanded
into a wide variety of financial services, such as checking, savings,
credit cards, mortgages, auto loans, student loans, and personal loans. 
For a time, this was quite successful.  However, the internet has
essentially driven switching costs to zero, and consumers increasingly
decide to do business with whichever firm is able to provide the best cost
for the best service.  Clearly, this unbundling has been to the benefit of
marketplace lenders, who have been able to deliver a positive customer
experience without the burden of legacy technologies, and whose operating
efficiency has allowed them to offer favorable rates.  As this new wave of
loan origination platforms grows to comprise a larger share of overall
lending, it will be interesting to observe if they are able to use
relationships and data to their advantage to make better decisions and win
the loyalty that had been so highly sought by traditional banks.
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Therese Torris's curator insight, July 29, 2014 3:44 AM

Interesting investigation of repeat borrowers at Prosper, trying to answer the question of whether online businesses are able to establish "relationship lending", i.e. Customer loyalty with positive impact

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Gareth Vaughan says P2P lending is an exciting financial services ...

P2P lending suffers from the same risks associated with any other credit provision institution, which include: identity theft, money laundering, terrorism financing, consumer privacy, and data protection violations.
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Things you might not know about P2P Lending

Things you might not know about P2P Lending | Orchard P2P Lending | Scoop.it
Fact on P2P lending (RT @kleverlaan: Things you might not know about P2P Lending (great infographics) http://t.co/Hag7aqCJ3E)
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Lending Club Going Public

Lending Club Going Public | Orchard P2P Lending | Scoop.it
After months of speculation about the when, Lending Club Corp. has started down the path to going public, tapping banks including Morgan Stanley and Goldman (Lending Club Going Public: The P2P lending platform connects investors to individual borr...
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