Industry Profile – Peter Renton

Often characterized as the industry’s biggest cheerleader, Peter Renton has become synonymous with marketplace lending. As the founder of Lend Academy Media, the LendIt Conference, and more recently Lend Academy Investments, Renton has served as a catalyst for the industry providing unprecedented insight and resources through his multiple platforms.  Despite Renton’s unwavering commitment to marketplace lending, his path to success was not always as straightforward and obvious as it seems in hindsight.

It all started back in 2008. Renton had recently sold his second printing business to a public company. While the enterprise had been successful, he was not particularly passionate about the printing industry  and eager to try something different.  Given that Renton was married and had two young children, he decided that his next venture would be an online business that he could manage from his home in Denver. With that in mind, he started looking at online businesses for sale.   

Renton was admittedly “all over the place” and remarkably broad in his search criteria.  In fact, one site that he very seriously considered purchasing was an online retailer that exclusively sold bamboo clothing—a far cry from marketplace lending. In a parallel universe, Renton could be an eco-conscious clothing mogul. However, as fate would have it, Renton happened across a magazine article about Prosper around the same time. “That article changed my life,” said Renton.  “I ripped the page out and immediately tried to invest. However, Prosper was in their quiet period at that moment.

“I had recently sold my business, had a whole bunch of cash, and interest rates were at a record low following the financial crisis.  I thought that the returns looked attractive on Prosper and I liked the idea of bypassing banks and connecting directly with borrowers.” Renton ended up investing with Lending Club at that point in time and eventually Prosper.  His confidence in the industry grew stronger as he was seeing increasingly good returns and more robust platforms.  Renton was fortunate to find a site called SocialLending.net for sale from someone who is now  an employee of Lending Club.  Renton’s full price offer was accepted and a business was born.  “What he doesn’t realize is that I would have paid him double,” joked Renton.

While Renton was fully committed to the site, he spent the following year learning more about the space, and laying the groundwork for what eventually would be rebranded as Lend Academy.  “It didn’t feel like a job, but I have never worked so hard in my life.” Equipped with his new platform, Renton was now faced with the challenge of building his audience and growing his business from the ground up. His comprehensive approach and determination are good reminders of how the best leaders are proficient in making their own luck. It is often said that luck is what happens when opportunity meets preparation. In Renton’s case, and most successful entrepreneurs, it would be pertinent to add persistence to the list.  

“I literally read everything about the industry. I also regularly produced content, commented on articles from other online publications, and did whatever I could as often as I could to get my name out there.” Given that the industry was still in its relative infancy, Renton was able to gain complete access to management of most companies and, almost by default, effectively developed strong relationships that would serve him well as his company and the industry began to scale. With regard to the growth of the industry, Renton’s tenacity began to pay off as traffic flooded into the site. On average, Lend Academy was doubling its audience year over year and quickly established itself as the preeminent resource for the online lending industry with Renton firmly in the center.  As the industry grew, so did Lend Academy and Renton’s influence. While a rising tide may lift all boats, it is undeniable that Renton was more than doing his part in making the waves.  

In January 2013 Renton was approached with an idea: to launch a conference dedicated to the burgeoning marketplace lending industry. While the event was conceived as the physical embodiment of everything Renton was doing with Lend Academy in terms of education and awareness, it would also provide a considerable networking opportunity for a diverse group of industry participants. Renton knew that they needed buy-in from Lending Club and Prosper in order to be viewed as credible. Successfully leveraging the relationships he had developed over the years, he gained support from both companies and the first global marketplace lending conference was born. The inaugural LendIt conference was held in New York in June 2013 and impressively sold out of all 350 tickets. “I couldn’t believe it,” said Renton, “we had to turn away 75 people!” Building on this success, Renton and his partners launched additional conferences in China and San Francisco and are bringing LendIt to Europe next month in London a logical progression given that the industry was essentially created in the UK.

More recently, Renton established Lend Academy Investments, with two of his LendIt partners, Bo Brustkern and Jason Jones. His latest venture seeks to ease the process of investing in marketplace lending across leading platforms by offering investment solutions to both accredited and non-accredited investors. “The idea actually came from our readers. They wanted to invest in the space but didn’t want to manage it themselves.” Given Renton’s experience covering lending and personally investing in the space, he felt that he and his partners could add significant value through this new platform and that it was a natural extension of the current business. While the applications of Renton’s knowledge and experience have evolved over time, education and advisement are still paramount to his vision and at the core of his growing enterprise as is evident with Lend Academy Investments.  

With all three business verticals flourishing, Renton now has his sights set on the future.  Discussing the outlook for next year and beyond, Renton believes that we’re going to see the first mutual fund in this space launch by the end of 2015. “If you look at the stock market, the vast majority of people are investing through mutual funds. Also, the U.S. has the mostly highly developed mutual fund marketplace in the world. I’m not sure who’s going to do it but I’m confident that most investors in the future will access this growing asset class through a fund.” To this point, Renton also mentioned that establishing a secondary market is becoming increasingly important in the industry to provide liquidity that doesn’t currently exist.

Renton also shared his thoughts on promising new platforms in the space that stood out from the crowd. “Upstart is a perfect example of someone who is not just a ‘me too’ player and who is extending the market. While they have some overlap with Lending Club and Prosper, they are underwriting in a way that is totally new.” Upstart is a lending platform that looks beyond credit scores and incorporates data like academic performance and employment history to offer better loans to recent graduates. “It’s definitely a company to watch,” says Renton.

Peering a little further down the road, Renton sees a forthcoming consolidation as the asset class matures. “Big companies will have no problem weathering the storm and many of the niche players will either be gobbled up or fail. Having a really strong credit team is huge, especially in the event of a downturn.” Interestingly, Renton also mused that the largest player in marketplace lending 10 years from now might not have even launched yet.  Nonetheless, he imagines that it will most likely be Lending Club, which he considers the “Google” of the space. “But,” he said, “you never know.” 

Orchard Platform Raises $12M in Series A Funding Backed by Spark Capital, Canaan Partners and Industry All-Stars

Today, we announced our Series A funding, which brings the total investment in Orchard to $14.7M. Not only am I thankful for the support of our existing investors, Spark Capital and Canaan Partners, which led the round, but I’m also excited to announce that they were joined by additional all-star investors John Mack, former chairman and CEO of Morgan Stanley; Hans Morris, former president of Visa and managing partner at NYCA; Nigel Morris, managing partner at QED Investors and co-founder of Capital One Financial Services; Anthony Abenante, former CEO of Instinet and senior adviser at KCG Holdings; Max Levchin, founder & CEO of Affirm, and former co-founder and CTO of Paypal; and existing investors Tom Glocer, former CEO of Thomson Reuters; and Vikram Pandit, Former CEO of Citigroup.

In covering the news of our funding this morning, the Wall Street Journal had this to say: “Veteran bankers—including John J. Mack , a former chief executive of Morgan Stanley; Hans Morris, who was president of Visa after a career at Citigroup Inc., and Capital One Financial Services co-founder and QED Investors Managing Partner Nigel Morris—are betting on a rapidly growing new financing model that links investors with loans posted online by individuals raising money for everything from refinancing credit cards to bankrolling small businesses.”

The interest from the venture community is yet another sign that marketplace lending has arrived as a compelling source of capital for a wide range of  borrowers. The products offered are unique and unmatched by anything currently available through traditional credit channels. What started off with peer-to-peer loans for consumers is now gaining traction in small business, real estate, and educational offerings. It’s an exciting time.

I see Orchard on the leading edge of this new frontier. We are in the early stages of a massive change to the credit markets and an overall transformation of lending. Our  goal at Orchard is to build the next generation of credit. Since founding the company one year ago, we have witnessed the emergence of a virtuous cycle that is driving benefits for all market participants. That’s a cycle that will continue, that investors want to be a part of, and that we’ll be ready to support today and into the future.

You can read our Series A press release to hear what our investors have to say about Orchard.

 

 

 

Consumer Credit Trends Q3 2014 - LendingClub Edition

Last week, we wrote a post on the growth and performance of Prosper’s lending marketplace.  We found that, in addition to the tremendous growth Prosper has shown over the last 2 years, the credit performance has actually continued to improve.  This week, we are reviewing similar metrics for Lending Club.  As we mentioned last week, 2014 has been a year of unprecedented growth in consumer marketplace lending.  As more borrowers and investors have learned of this new asset class, new loan origination volumes have increased at an impressive rate.  Many investors and observers understandably wonder whether originators have been able to maintain their standards amidst this growth or if the expansion has come at the expense of credit quality.  In today’s analysis, we will explore the credit characteristics and repayment performance of recent LendingClub vintages.  

Lending Club’s historical loan book is delayed by 3 months, so we will be looking at growth volumes as of June 2014.

A Time of Growth

LendingClub originated just over $1 billion in loans in the 2nd quarter of 2014, up from $791 million the previous quarter and $446 million in Q2 2013.  The graph below shows the growth in quarterly originations for prime consumer loans, the largest portion of LendingClub’s portfolio, as the data on Springstone, near-prime, and small business were not publicly available.

Distribution By Credit Grade

The graph below shows the proportion, by LendingClub’s credit grade, of monthly originations.  The distribution has been extremely stable, which is what we expected given the consistency we’ve seen in LendingClub’s borrower profile and underwriting strategy over the past two years.

Credit grade, of course, is Lending Club’s own internal measure of credit risk.  It is prudent to compare this to a stable, externally-defined measure of risk, such as FICO.  The graph below shows an impressively consistent distribution of FICO scores, with ~40% of borrowers having a FICO > 700.

Vintage Performance

Finally, we review the vintage performance.  What we show here are the cumulative 30+ day delinquency rates for all LendingClub loans originated between January 2008 and March 2014.  Remember that these curves include all loans that ever were 30+ days past due, many of which do not actually charge off.  Nevertheless, it is useful to use this “early warning” metric to be able to examine the performance of more recent vintages that may have not be seasoned enough to have statistically significant charge-offs.

This graph shows essentially every vintage of loans performing better than the previous, with loans issued this year trending as the best vintage to date.  This is quite a testament to the resources that the LendingClub team has devoted to refining their underwriting.  By focusing on the quality of their borrowers, LendingClub has proven that rapid growth in lending can be accomplished without sacrificing performance.

Conclusion

As we have seen, marketplace lending has been growing at a rapid pace over the past few years.  This growth has brought both LendingClub and Prosper from being nichey, obscure options to serious lenders, providing much-needed lending products to borrowers across the credit spectrum.  However, the fast pace of their growth is actually not the most impressive fact about these 2 loan originators.  The quality and restraint with which they have been able to do so is the truly impressive feat.  

Now that the business model of marketplace lending has demonstrated its value, additional originators are quickly emerging across a full range of consumer and commercial credit products.  We truly hope that all participants in this market will adopt and maintain a program of smart, robust, and data-driven risk management, just as we have seen from the industry’s pioneers.  At Orchard, this is a top priority in our evaluation of each new originator with whom we do business.  We are optimistic for the continued success of this movement and excited to do our part: providing institutional investors with the technology and analytics they need to effectively deploy capital and working with originators to accelerate their growth with a marketplace of investors.

 

Consumer Credit Trends - Q3 2014 Update

Just three months remain in 2014, a year that has seen unprecedented growth in consumer marketplace lending.  As more borrowers and investors have learned of this new asset class, new loan origination volumes have increased at an impressive rate.  Many investors and observers understandably wonder whether originators have been able to maintain their standards amidst this growth or if the expansion has come at the expense of credit quality.  In today’s analysis, we will explore the credit characteristics and repayment performance of recent vintages.

A Time of Growth

As we can see in the graph below, Prosper originated $171,632,807 in September 2014, up from $167,568,939 the previous month and $30,701,053 in September 2013.

Distribution By Credit Grade

The graph below shows the proportion, by Prosper’s credit grade, of monthly originations.  In spite of the tremendous growth we’ve observed, the distribution has remained remarkably similar month over month.   

Credit grade, of course, is Prosper’s own internal measure of credit risk.  It is also prudent to compare this to a stable, externally-defined measure of risk, such as FICO.  The graph below shows that the distribution based on the externally-defined score is also stable.  Keeping a stable distribution, while maintaining such steady growth is not easy and requires careful underwriting.

When we look at the distribution of FICO by credit rating, we see that Prosper has clearly done some adjusting within the credit model, but the distribution is still fairly consistent.

Vintage Performance

Finally, we review the vintage performance.  What we show here is the 30+ day delinquency rates for all Prosper loans since 2008 - 2014 Q1.  What we see is that 2013 and Q1 2014 are the best performing vintages so far.

This trend also is the case within most of the different credit grades, meaning that the improved performance is across the board.  

Conclusion

As we saw in the recent financial crisis, it is easy for loan originators to expand into bad loans in order to grow volumes.  In many cases, this is cheaper than the expense of marketing to and acquiring more credit-worthy borrowers.  However, with marketplace representing such a tiny piece of consumer lending, there is a lot of good still out there, and we’re nowhere near saturation.  Additionally, the products offered by Prosper, Lending Club and other emerging marketplace lenders such as Karrot (launched by the team behind Kabbage), Best Egg, Pave, Upstart, Circleback, and Peerform, are unique and unmatched by anything currently offered by traditional banks.  We look forward to continuing to monitor the volume, distribution, and performance of all of these marketplace originators.

Semantic Classification and Consumer Lending

In the early “peer to peer” days of marketplace lending, many investors were drawn in by the ability to research the credit profile of each prospective borrower and read a detailed description of a loan’s purpose.  Anyone in a state that allowed P2P investing could become a loan officer from the comfort of one’s own home, individually reviewing loan applications, making a judgment as to risk vs. reward, and choosing whether or not to invest in the funding of a given loan.  

As the industry has evolved and grown, large investors have come to rely on algorithms rather than human-driven loan-by-loan analysis, and the major consumer marketplace originators have in fact removed these lengthy borrower loan descriptions from their websites and data feeds.  Nevertheless, the long history of borrower loan descriptions and subsequent credit performance provides a valuable corpus of data.  We can use this information to understand the association between language and loan performance as well as to develop a framework for the use of language processing in the evaluation of consumer and small business loans offered by originators that do include these features.

What Do Borrowers Have to Say?

To conduct our analysis, we constructed a dataset of just over 100,000 loans offered on major consumer marketplace lending platforms.  In order to analyze the language contained within these loans, we had to first conduct some text-sanitization, in which we programmatically converted all text to lowercase, eliminated extra spaces and punctuation, and removed certain English “stop words” from each description.

Common English Stopwords - Source: http://www.nltk.org/

After removing the “stopwords”, we also applied a “stemming” algorithm to remove prefixes and suffixes from words.  For instance, “quick”, “quickly”, and “quicker”, would now all become “quick”.  

The word cloud below shows the 500 most commonly used words, with size indicating their relative frequency.

Word Frequency and Incidence of Default 

To gain a sense for which words were associated with better or worse loan performance, we calculated a “bad rate”, defined as the percentage of loans whose description contained the word that went 30+ days past due, defaulted, or charged off.

The 2 charts below show the words with the highest and lowest bad rates.

Using Text Analysis to Predict Risk

Given the extensive corpus of linguistic data and loan performance information, we were able to build a ranking system using a technique known as a Bayesian classifier.  This is the same basic approach used by email spam filters to assess the probability of an email being spam.  The technical detail behind how we built this and the way it works will be the subject of another post, but the results are rather striking.  We used a Bayesian approach to give each loan a “word score” corresponding to a probability of default as a function of the text patterns in its description.  Next, these scores were grouped into deciles and plotted against credit grades.

The graph below shows that a score based on text classification has the power to effectively rank both overall as well as within credit grades.

Conclusion

While LendingClub and Prosper have removed their detailed loan descriptions, some other marketplace lending originators emerging in the U.S. and around the world do include text-based information from prospective borrowers, particularly those offering small business loans.  As marketplace lending evolves, so will the technology and data available to investors.   Machine-based text analysis is another example of taking a process that was once time-intensive and could only be done by human beings and using modern resources to make it scalable and more accurate.  Ultimately, the ability to rapidly and accurately assess risk using a diverse set of data will lead to greater liquidity for consumers and businesses as well as the more efficient allocation of capital across our economy. 

Comparing Prosper and FRED Economic Data

We’ve written in the past about borrower income and debt levels and how these variables predict risk of default.  In those analyses we assessed whether a borrower with a larger debt to income (“DTI”) ratio is more likely to default on a loan payment.  We found that DTI and disposable income are both predictive.

These analyses are useful when developing an investment strategy, as they help identify borrowers that are more likely to default.  Last week, a friend shared some interesting data from Federal Reserve Economic Data (FRED), a robust database maintained by the St. Louis Federal Reserve Bank; the database includes almost 150,000 economic time series data from nearly 60 sources.  The specific data measures Household Debt Service Payments as a Percent of Disposable Personal Income.  In other words, the trends in the United States over time of debt payments to disposable income (i.e. income after taxes).  The graph below shows this metric over time, which has been dramatically decreasing in the recent years.

Over the past 6 years, this metric has gone from a 30-year high of 13.2% to a 30-year low of 9.9%.  This volatility is result of the credit bubble leading up to the 2008 recession and the subsequent household de-leveraging during the 2010 to 2014 gradual economic recovery.

Given that marketplace lending has grown during this time period, we wanted to assess what trends exist with the borrowers on Prosper and how Prosper borrowers compared to the nation as a whole. 

In order to conduct this analysis, we first had to identify the inputs:

Debt: Given that all of the borrowers applying for loans on Proper have a credit bureau pulled, assessing the monthly debt payments is easy.  In fact, Prosper provides a variable called "monthly debt" through their API; this is exactly what we need.   

Disposable Personal Income:  Prosper provides "stated monthly income". However, this is the borrower’s gross income.  In order to calculate FRED’s definition we must take 72% of that income to account for taxes.

Some important pieces of information to keep in mind when analyzing this data are:

1.    The inputs may not be apples to apples.  FRED data is pretty clear, as is Prosper’s, but ensuring that they are measuring the same things in the same way is impossible. 

2.   FRED data is looking at the country overall at a snapshot in time, while Prosper’s data show the loans originated at that time.  Prosper does not provide periodic updates as the borrower’s income and debt change over time, so it would be difficult to measure the DTI for the platform as a whole without making many assumptions.

With those caveats in mind, we will compare DTI for Prosper v. the FRED data over the past 3 years.  We find that the median Prosper borrower has a higher DTI than the overall country.  This is not surprising given that the majority of borrowers are applying for a loan in order to consolidate debt.  The average Prosper borrower DTI remained in the ~15% over the last few years. 

To further analyze this data, we reviewed an additional time series published by FRED: the real disposable income per capita.  Income per capita has been around $37,000 for the past year, meaning the average per capita monthly household debt service payment is $306. 

Next we compare the per capita income from FRED to Prosper for the same time period we used to assess DTI.  

The average income for Prosper is $56,000, putting the monthly debt service payment at $827.  The average Prosper borrower’s income is 51% higher than the average American household.  This difference is significant and is likely one of the drivers for Prosper’s low observed and predicted defaults in the most recent vintages, despite the higher debt amounts.

There are many sources of economic data out there, and while some might be more useful than others, it is valuable to analyze and assess how marketplace lending borrowers compare to the general population.  Such data can be used to compare and assess various marketplace originators’ platforms and underwriting strategies.  It can also be used to develop benchmarks for an investment strategy.  If nothing else, it helps to understand economic trends that affect all asset classes. 

Industry Profile – Albert Periu

It’s been a big year for our friends at Funding Circle. As one of the global leaders in small business lending, the company is fresh off of a $65M funding round and acquisition of LeapPay. A prominent force behind this success and rapid growth is Albert Periu, Director of Capital Markets for Funding Circle in the US. Albert was kind enough to take the time to speak with us about his experience and what makes Funding Circle so special. 

In his role, Albert leads the investor sales team and is responsible for the structuring, execution and distribution of Funding Circle’s offerings to institutional and accredited investors.  Albert came to Funding Circle through a merger with the San Francisco-based Endurance Lending Network in 2013, a partnership that enabled Funding Circle to penetrate the rapidly growing US market. Asked to describe the ongoing operations and collaboration between the US and UK business units, Albert remarked “I like to joke but it’s true — it’s as if two lenders got married. We have a lot in common and there’s a tremendous amount of learning from both sides.” Applying some of the learnings from the across the Atlantic, particularly from an underwriting and operational perspective, helped Albert and the rest of the Funding Circle team accelerate growth in the US market. “It was helpful to learn from their mistakes [not that they made very many],” says Albert.

However, before Albert entered the world of disruptive financial technology, he cut his teeth at several more traditional financial institutions. After graduating from Georgetown University, Albert launched his career as an investment banker in the Global Media Group at Deutsche Bank and then Merrill Lynch. Following, Albert shifted his focus to institutional sales holding positions as Vice President at FBR Capital Markets servicing hedge funds, family offices and asset managers and more recently as Director at Telsey Advisory Group. By amassing an arsenal of experience across the financial services sector, Albert was able to comprehensively learn how banks work — what they are good at and also what they are perhaps not so good at. One thing that was made abundantly clear to Albert was that there was a fundamental need to fill the gap in small business lending. Having come from a family of small business owners, Albert had intimate knowledge of this sector — how it should be serviced and the potential opportunity. His passion for small business combined with his capital raising and sales experience is what ultimately brought him to Endurance and is what has allowed him to be a driving force in the rapid growth of Funding Circle in his role as Director of Capital Markets. In reference to the transition from traditional financial services to FinTech, Albert articulated that he enjoyed being part of small team of seasoned, experienced people. “It was a big change for me, but I’ve found it to be very refreshing to be on a different side of the industry that is working hard to help small businesses grow.” 

The alternative lending space, in particular small business lending, has become increasingly crowded given the success of companies like Funding Circle. Albert maintains that Funding Circle has been able to differentiate themselves by exclusively focusing on small business loans and providing a simple, fair, and efficient process. In fact, Funding Circle is now the leading small business loan marketplace in the world. Unlike some of the other lenders, Funding Circle offers a true bank replacement loan with human underwriters who actually speak with the borrowers.  Albert argues that a common misconception about Funding Circle is that they make loans that banks don’t want to be making and that its borrowers are not quality ones. However, they actually make loans that banks should be making but are unable to pursue due to archaic credit models and bureaucratic red tape. “I think that people are beginning to realize that this should be part of the normal process — that we work together with banks, not against,” says Albert. He reasons that education and awareness play a big part in continuing to grow the industry. “Transparency is a big issue,” says Albert.  To facilitate this, Funding Circle has been publishing more content on its website covering fee structure, new products, successful funding stories, and thought leadership. Albert and other team members also regularly attending industry conferences and events. 

Outside of building a better financial world for lenders and borrowers at Funding Circle, Albert enjoys spending time with his wife and two dogs — a Jack Russell and a rescued mixed pup.  When not volunteering at the San Francisco ASPCA, Albert likes to take advantage of the great outdoors and hiking around the Bay area.

Funding Models For Loan Originators

Since starting Orchard, I have had hundreds of conversations with loan originators of all sizes. One common theme to the conversations surrounds the various options they have to fund their loans. If we look back one year, the conversation centered around whether LendingClub’s Marketplace Model was better than the traditional balance sheet and securitization models. Both sides had valid points, so the arguments would quickly become passionate at industry events.  

In the past 6 months, the conversation has shifted, as originators have started to blend the different models and holistically reconsider how loans are funded. The question has shifted to become: “what are the best funding models for the different types of loans I originate today, and what are the best funding models for the loans I want to originate in the future?” In order to answer these types of questions, it is best to look at the strengths and weaknesses of each funding model:

Balance Sheet - Originators fund their loans on their own balance sheet

  • Pros: Originator captures all of the yield, and loans can be funded quickly.
  • Cons: It is very difficult to scale, since the originator must sell equity to increase its balance sheet to fund additional loans.

Credit Line - Originators borrow money from a bank to fund their loans

  • Pros: Originators can increase returns by utilizing leverage.
  • Cons: Covenants can be very restrictive on the types of loans eligible for funding, and there is a risk of the credit line being pulled during a financial crisis.

Securitization - Originators create a large pool of loans and sell securities against this pool    

  • Pros: Reduced cost of capital to fund loans.
  • Cons: Securitization markets have cycles, and it is not a consistently reliable method over long periods of time. It can also take months to build a large loan pool for securitization.

Marketplace - Originators fund their loans through a marketplace

  • Pros: Originators can introduce new loan products very rapidly, as their loans are completely funded by a diverse pool of multiple investors.
  • Cons: Revenues are limited to origination and servicing fees, since the yield is going to marketplace investors.

We believe successful originators will use many if not all of the funding options, since each has different strengths and weaknesses. Right now, the Marketplace model is limited to a handful of early adopters, but their successes are convincing originators of all sizes to strongly consider the marketplace model. At Orchard, we are building technology that makes it easy for originators to adopt the marketplace model because we believe it will play a crucial role in all originators’ funding strategies.

 

The Orchard Lendscape

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. While loan originators like Lending Club and Prosper may be well recognized, others in the space — including institutional investors, credit scoring companies, credit data providers, loan servicers, and providers of custodial and administrative services — are less well known.


Together, these companies make marketplace lending possible. While the Lendscape can never reflect the full diversity of the market, it does provide a helpful overview that illustrates the flow of funds and information within the industry. As the market continues to evolve and grow, Orchard will update the Lendscape to reflect those changes.

Back to School – Financing Education With Marketplace Lending

Whether you are a young man or woman heading off to college or an adult whose school days are a distant memory, the month of September carries a familiar association: back to school.  The years we spend in formal education can be among the most transformative and memorable of our lives.  Nevertheless, the rising cost of education has sparked debate in the United States and around the world.   In today’s analysis, we examine the role marketplace lending might play in the financing of education.

In our recent analysis on real estate lending, we included the following graph, showing the major sources of U.S. consumer debt as of 3/31/2014.

Source: U.S. Federal Reserve, 3/31/2014

As of this June, the U.S. Federal Reserve put the balance of outstanding student loan debt at $1.27 Trillion, exceeding the levels for other common sources of spending, including auto loans and credit cards.  Perhaps some students will be turning to marketplace lenders to obtain the funds necessary for their education.   

Education Loan Volumes

While overall educational lending has increased in the United States, leading marketplace lenders LendingClub and Prosper both stopped making education-purpose loans on their platform in 2010.  This is due to certain provisions of federal law surrounding loans for “post-secondary education expenses”.  Loans for this purpose are subject to conditions beyond those required of other loan purposes, making such loans incompatible with the structure of P2P lending platforms.

 Given the lack of data available from U.S. platforms, let’s instead take a look at Europe.  Bondora, the rapidly-growing pan-European marketplace lender, does offer loans for educational purposes, and while the volume for this purpose is still quite small, it does make available some compelling data that should give us a sense of these borrowers and their profile.

Bondora Education Loans – Demographic Data

In the chart below, we show 2014 Bondora loans by country.  Estonia and Spain are the clear leaders, with Spain surpassing even Bondora’s home country. 

As interest rates tend to vary by locality, it is useful to examine the distribution of interest rates by country (excluding those with very low volume).  In the graph below, we can see that rates range from 12.5% to 37.5%, with Estonia having a somewhat wider distribution than Spain.

In the graph below, we compare the interest rates of education loans to those of non-education loans.  There does not appear to be a much of a meaningful difference.

In the way of demographics, Bondora also happens to make available certain data that is typically harder to come by in the U.S., including education, age, gender, and marital status.

 

Credit Quality and Performance

As the increase in education-purpose loan volume on Bondora has been relatively recent, we are not yet in possession of enough performance data to truly compare this versus other loan purposes.  We plan to check back in 6 months or so to conduct a more thorough analysis.

Conclusion

While LendingClub and Prosper stopped making education-purpose loans in 2010, there is certainly a desire in the alternative lending community to fund education.  Companies such as Commonbond and SoFi have been lending to people for the purpose of paying for school or refinancing student loans, with notable success.  There are also some companies introducing loan products for very specific educational uses, such as to fund attendance at various coding schools.  Needless to say, we’d love for some of these companies’ data to be publicly available so that we could understand the borrower dynamics and loan performance.   While we are in the early days of applying marketplace lending to education, we are optimistic about the potential for simpler and more efficient student lending. 

The Economic Health of a Borrower’s City Affects Loan Performance

Harlan Seymour runs a family office in San Mateo, California, with a primary focus on analyzing and investing in fixed income instruments, including marketplace loans.

Introduction

Marketplace lenders like Lending Club and Prosper provide dozens of data points about a borrower’s financial situation.  In an attempt to improve upon average loan performance and generate “Alpha”, sophisticated investors crunch this data to select loans that have been graded more harshly by the lender than the data warrant.

One of the data points provided is the borrower’s locality (city and state).  Analyzing historical loan data shows that, all else being equal, loans issued to borrowers living in economically prosperous cities significantly outperform, while those from troubled localities underperform.

Locality Database

We have created a locality database containing geographic, economic and demographic information for the U.S. as a whole, for all 50 states (plus Washington, D.C.), for all of the over 3,000 U.S. counties, for over 50,000 cities, and for thousands of neighborhoods within larger cities.

Borrowers enter their city and state in their loan applications.  Many borrowers use their neighborhood name as their city name.  For example, Venice Beach, CA is actually a neighborhood of Los Angeles.  Knowing the neighborhood is useful, since economic data (like real estate prices) is available down to the neighborhood level.

We examined the 333,134 loans issued by Lending Club through June 30, 2014.  Using the locality database, we were able to match 99.1% of the cities entered, with many of 0.9% unmatched cities being misspellings (that we decided not to pattern match).  2.6% of the cities matched actually turned out to be neighborhoods:

15,144 individual cities and 161 neighborhoods were matched within the historical loan data.  Using the latitude and longitude of these cities and the loan count for each city, we created a heat map of where borrowers are located (# of loans per city is color coded):

Locality Health Score (LHS)

The locality database contains a rich set of current and historical, economic and demographic values for the U.S. itself, as well as for the neighborhoods, cities, counties and states it contains.  Such values include home prices, unemployment rates, labor force participation, per capita and household incomes, populations, etc.  An optimized weighted average of these values was formulated to create the Locality Health Score (LHS) that runs from 0 (bad) to 1 (good) for each locality. 

As of January 1, 2014, these are the top and bottom 8 U.S. cities with populations over 500,000, as measured by the LHS:

8 top-rated cities

8 bottom-rated cities

LHS vs. Loan Performance

We used Lending Club’s June 30, 2014, historical loan snapshot to analyze how the LHS relates to loan performance (overall default rates) over the lifetime of the loans.  Specifically, we focused on grade A-D loans from 2010-2013.  For the 2013 cohort only “seasoned” loans issued in the first half (H1) of 2013 were included in this study.

Cohorts were broken down by year and grade.  In each cohort, loans with a high LHS (> .8) and loans with a low LHS (< .3) were compared to the overall cohort.  We measured the fraction of bad loans in a cohort as:

(# in grace period + # in default/charged off) / (# loans in cohort)

The results show that high (> .8) LHS loans result in a reduction of the percentage of “bad loans” in every cohort (all years, all grades).  Conversely, low LHS (< .3) loans experience an increase in the percentage of “bad loans” in every cohort (all years, all grades).  Thus, the LHS is highly relevant for marketplace loan selection.   

This chart shows that for every year, 2010-2013, an LHS < .3 (in red) significantly increases the fraction of bad loans vs. the overall fraction (in dark grey), and that an LHS > .8 (in green) significantly decreases the fraction of bad loans:

These charts show that these results are consistent across all years (2010-2013) and all grades (A-D):

How to Use LHS When Investing in Marketplace Loans

My family office invests in marketplace loans using highly tuned filters for selecting “good loans” that should default at a rate significantly lower than other loans of the same grade or interest rate.  The LHS plays a part in these filters.

Since we invest in fractional loans (vs. whole loans), we mainly use the LHS to vary the amount we invest in a given loan: the higher the LHS, the higher the fractional investment.  This biases our marketplace loan portfolios towards borrowers in prosperous localities.  When the next economic downturn comes, borrowers in prosperous localities should be more resilient.

Conclusion

The city or neighborhood in which a borrower resides turns out to have a meaningful impact on the rate at which a borrower may default on his loan(s) versus loans to other borrowers of the same grade.  Furthermore, in an economic downturn, borrowers in more prosperous cities may be more resilient than those in troubled cities.  With the Locality Health Score (LHS), we have developed a single number that coalesces several economic and demographic values for a locality into a simple-to-use and understandable number, ranging from 0 (bad) to 1 (good).

 

August 2014 Marketplace Lending Monthly Recap

Month and Year-to-Date Asset Class Returns 

The Orchard US Consumer Marketplace Lending Index outperformed three of the five comparable U.S. fixed-Income asset classes for the month of August. The Orchard Index outperformed 3-5 year Treasuries, 3-5 year Investment Grade Corporates, and 5-year Municipals and underperformed Intermediate High Yield Corporates and Securitized Products for the month.  

Source: Fixed-income asset class returns based on Barclays Benchmark Indices

Source: Fixed-income asset class returns based on Barclays Benchmark Indices

However, on a year-to-date basis, the Orchard US Consumer Marketplace Lending Index continues to outperform all five comparable U.S. fixed-Income asset classes.

Source: Fixed-income asset class returns based on Barclays Benchmark Indice

Source: Fixed-income asset class returns based on Barclays Benchmark Indice

LendingClub – Pioneering Marketplace Lending & Reshaping Financial Services For Years to Come

In a move promising to transform the landscape of global finance for years to come, LendingClub, the leader in the nascent field of marketplace lending, recently filed for its initial public offering.  Having now made over $5 billion in loans, the success of this booming fintech juggernaut might now seem inevitable.  At this time, however, it is important to understand the state of the world when LendingClub opened its doors, the driving forces behind the need for a new approach to consumer lending, and what this watershed event means for the future of global financial services. 

Rebuilding Real Estate With Marketplace Lending

At $8.2 trillion in the United States alone, mortgage debt dwarfs all other asset classes within consumer credit.  As marketplace lending has grown, its potential to transform the allocation of capital has captured the imagination of an industry, and, increasingly, the public.  While this new way of lending has largely grown around unsecured consumer and small business lending, several exciting companies are working to extend marketplace lending to real estate, an effort that, if successful, promises to have far-reaching implications for our economy.

Source: U.S. Federal Reserve - Data as of 3/31/2014

Many of the circumstances that have necessitated rethinking in the financial world apply particularly to real estate.  If bureaucracy, regulation, outdated technology, and less-than-stellar customer service exist anywhere in banking, they definitely exist in the mortgage process.  As anyone who has been through the process of obtaining a residential mortgage in the past several years can attest, it is not particularly easy or pleasant.  These hurdles apply to commercial real estate as well.

As with any nascent industry, new entrants are offering a diverse set of business models.  Below, we explore some of the most common and interesting examples of how real estate lending is being transformed and democratized through technology. 

Debt Crowdfunding of Real Estate Projects

If you walk around any town or city in the United States, chances are that you will see a residential real estate project.  This might be the construction of a new home or apartment building or the renovation of an investment property.  An example of this is a “flip”, in which an investor purchases a property, renovates it, and then sells it at a (hopefully) higher price a short time later.  A developer will need a sizable chunk of capital to finance such a project, the source of which has traditionally been from personal savings, family and friends, or various “hard money lenders”.

Now, developers have the option of obtaining project funding through an investor marketplace.  On sites including Patch of Land and RealtyMogul, real estate developers can apply for loans to fund their projects through a streamlined, online application process. 

The loans that borrowers receive are typically of 3-12 month duration, with APRs in the 10-20% range.  The investor experience, while maintaining some parallels to unsecured consumer marketplaces such as LendingClub and Prosper, is significantly more specialized to real estate.  Investors can avail themselves of a lengthy project description, property photos, appraisal information, developer biography, construction budgets, financial projections, and risk data.

Equity Crowdfunding of Residential and Commercial Real Estate Projects

It is common practice for any real estate development to be structured as its own corporation, typically an LLC.  In equity crowdfunding of real estate, as practiced on platforms such as RealtyMogul and Fundrise, investors can purchase shares in one of these LLCs.  Shareholders are then able to earn a portion of the cash flow that is generated from a property (e.g. from rental income) as well as the proceeds of the property’s eventual sale.  While equity investing in real estate clearly carries risk, it also affords the investor the opportunity of benefitting from a property’s appreciation in value over time.

Online Mortgage Lending

While the aforementioned categories are very compelling, neither sounds quite like what most people think of as a “mortgage”.  If marketplace lending can transform the way that ordinary people finance their primary residences, it will be a truly great accomplishment.  LendingHome, LendInvest, and Privlo all promise great strides here. Privlo is doing this today, though only in Texas and Idaho at the current time (the others do not yet allow loans on owner-occupied properties). Privlo lets borrowers apply for a mortgage online and also has a “concierge” to walk applicants through the parts of the process that require a human touch.  Borrowers can be approved for a 5 or 7 year adjustable rate mortgage with down payments of at least 20%.  Unlike with traditional banks, the submission and review of documentation is performed entirely through an online portal, a welcome respite from the endless faxing or overnighting of paper experienced by most mortgage-seekers.  Privlo’s value proposition sits with its ability to use data and proprietary algorithms to qualify borrowers who might otherwise have trouble securing a mortgage, albeit at slightly higher than average rates.

Early Days – Challenges & Scale

Changes in a multi-trillion dollar, highly-regulated industry do not come easily.  Indeed, there are quite a few challenges that these new lenders will have to tackle in order to scale their businesses.  The involvement of the U.S. government in mortgage lending casts a long shadow, including a patchwork quilt of federal and state regulations.  By some estimates, Fannie Mae and Freddie Mac guarantee 77% of all mortgages originated in the U.S.  If you include Ginnie Mae, which guarantees loans made by the Federal Housing Administration, that number jumps into the nineties! 

In addition, few of the loan structures available in this market today resemble a traditional mortgage.  One key contributor to that fact is that of loan duration.  While the archetype of an American mortgage is a 30-year, fixed-rate loan, few investors would fund such a loan without a way to create shorter-term liquidity.  In traditional mortgage finance, liquidity is achieved with securitization and secondary loan trading.  As these innovations make their way into marketplace real estate lending, we will likely see things open up for longer duration loans and higher volume. 

Perhaps the most interesting challenge is the fact that we are dealing with an asset that exists in physical space.  As the old saying goes: “location, location, location”.  Real estate markets are highly local, and many investors want to examine a property in person, only wanting to invest in areas where they have a knowledge of market dynamics.  It remains to be seen if investors will be content with online photos and rich web-based content, particularly for properties not close to home.

For many people, a home is both their most expensive purchase and their largest investment.  With mortgage lending as a $8.2 trillion industry, this is perhaps one of the largest and most important sectors ripe for disruption as marketplace lending continues its forward march.

Industry Profile – Zhengyuan Lu of OnDeck

Briefly describe your career and how you came to work at OnDeck?

I have been in the capital markets space for nearly 20 years. Prior to OnDeck, I was a Managing Director of the Asset Finance Group at Gleacher & Company; Managing Director and Head of Structured Products Group at Keefe, Bruyette & Woods; SVP at Fortis Securities and WestLB AG; and Portfolio Manager at PPM America.

You come from a traditional finance background. How has the transition been to a tech company?

The transition has been exciting and OnDeck has been an eye opening experience for me.  While OnDeck has many similar characteristics of traditional lenders that I used to advise, the tech aspect makes OnDeck extremely unique. There is a tremendous amount of electronic data about small businesses that traditional lenders are ignoring or unable to process. Through our technology platform, we are able to digest and analyze a significant amount of data in real time, which allows us to make better credit decisions faster.

What do you like most about working at OnDeck?

It’s inspiring to be a part of a company that is helping small businesses succeed and our economy grow. We are on the forefront of fundamentally transforming an antiquated lending system through technology. 

How does OnDeck differentiate itself from the other online small business lenders?

We’re doing two things to disrupt the industry: we’re making short term working capital more accessible and we’re making the process faster so business owners can spend their time growing their business instead of trying to find financing.  First, our OnDeck Score enables us to make capital more accessible by incorporating business operations and performance data to more accurately assess a business’ health. Second, we’ve deployed a proprietary technology that delivers speed and convenience to small business owners, as well as superior service they deserve. We find that business owners generally want to speak to someone about their loans and so we have loan specialists available Monday through Saturday to talk to customers about their needs and options. 

What is one common misconception people have about OnDeck?

Many of our customers think we are similar to banks. They know we are more tech enabled than banks, but they are blown away with just how fast and easy the process is. We have a 10-minute, online application process (vs. days or months of bank paperwork) and we evaluate small businesses using thousands of data points (vs. relying heavily on business owners’ FICO scores).

What projects are you working on that have you particularly excited?

Our mission at OnDeck is helping small businesses, and small businesses have many financing needs. We are constantly testing new features and products to better serve small businesses, and I am focused on making sure we have flexibility on the financing side to meet all their needs.   We are also growing OnDeck Marketplace, where institutional investors can buy loans we originate directly. Accessing the securitization market is another big step in executing OnDeck’s financing strategies. Through securitization, we are able to continue improving our financing terms while diversifying our investor base, which significantly benefits all key stakeholders in the business.

Education is a big part of growing this industry. What is OnDeck doing to facilitate this?

Educating small businesses is very important to us. When we launched, the direct lending space was in its infancy. Most small business owners were not aware of alternatives to banks. Over the years, we have increasingly added new educational resources for our customers. For example, we have a blog and newsletter that distributes daily tips such as how to apply for a loan and how to better manage your business. We also host OnDeck events and have partnered with organizations such as SCORE to provide small businesses with resources they need to make vital business decisions. 

Are there any other companies in the space that you think are doing very innovative things?

There has been a secular change in the lending space.  Similar to OnDeck innovating the small business lending space, companies like LendingClub, Prosper and SoFi are changing the landscape of the personal lending space.  It is an exciting time for our industry. 

What’s next for OnDeck?

OnDeck’s vision is to transform how money flows to small businesses by leveraging our platform to enable all types of investors to make capital on demand a reality for small business owners. Think of how Priceline transformed travel, or Zillow has transformed home buying – we believe small business financing can be ongoing and friction-free. We’re excited to continue to bring new products to market for our customers and really be a partner to small businesses throughout their entire lifecycle.

What’s next for Zhengyuan Lu?  

My main focus on the capital markets side is to build the most durable and scalable financing platform to ensure that small business can always have access to capital from OnDeck.  We have made significant progress over the last couple of years, and the work is never done. 

What do you do for fun outside of work?

I am an avid traveler.  We started a summer tradition of seeing a new country every year since my youngest turned 4, and he is 11 now.  I am also addicted to running on the weekends.  I think running is therapy for the mind.

Do you have any favorite restaurants?

I live in Chappaqua, and we love Le Jardin Du Roi in town, a small family owned French bistro.  They serve very rustic French food that brings you back to south of France, and they always treat you like a family. 

Do you have any unusual talents?

When my kids were little, I started learning small magic tricks to amuse them.  I kept it going over the year so I have accumulated a lot of magic tricks.

 

 

Discussing the Small Business Lending Evolution

The history of business lending is as old as the earliest societies, and the related innovations are innumerable.  From the interest bearing loans issued in ancient Greece that made lending profitable for investors, to loans secured by collateral in the 1800s that made lending more secure for investors and therefore more affordable for borrowers, to the founding of the Small Business Administration (SBA) in 1953, which established that lending to small businesses is an important feature of our economy.  The landscape has been ever evolving.  The lending products available to a business owner today range from standard loans with a fixed interest rate and term to a merchant cash advance that automatically deducts loan payments from credit card receipts to lenders underwriting loans based on programmatic connections to the borrower’s Etsy account.

Given the size of Prosper and LendingClub, it may seem that the roots of online lending are in consumer lending, but there have also been many small business lenders innovating in similar ways for over 10 years.  There has been a recent storm of publicity and big news from these lenders, including the following:

Why is this an area so ripe for these new entrants?  Banks have traditionally been the go-to place for small businesses to borrow.  However, as businesses change and grow, so do their financing needs.  Making a credit decision on a small business is difficult.  The business’ finances are inherently combined with the personal credit of the owner, leading to questions about what to focus on in an underwriting strategy.  Most traditional lenders will look at some basic metrics on a business to make an underwriting decision (e.g. time in business, industry, revenues, business credit information, and the personal credit of the owner).  However, some of this data is not easily available or verifiable.  Revenues, for instance, can be verified by obtaining audited financial statements, but not all business owners have these, and reviewing them requires the work of a trained analyst.  The availability of alternative data via APIs (and other methods) has enabled lenders with the technical prowess to access and make sense of it in order to lend to businesses that, using traditionally available data, may have been declined.  Most of the companies listed above are pursing such an approach to small business credit underwriting.

Reviewing data from the FDIC, we see the trends over the past 10 years in bank lending to businesses.  Lending by the banks in the <= $1MM loan size segment (generally what is considered to constitute a small business loan) has decreased steadily since the peak in 2008. 

Digging deeper, we see that the $100K - $250K & $250K - $1MM segments follow this trend as well:

However, the < $100K segment displays a very different trend, with loan balances decreasing almost every month since 1995.

Given that the lenders discussed here are generally operating in this segment, it is clear they are positioned to fill an ever growing void.

Loan volume trends for the companies discussed here are not easy to find.  According to the Wall Street Journal, Business Financial Services estimates that online nonbank lenders provided ~$3B in loans in 2013.  Assuming this is mostly in the <$100K segment of lending, it comprises a significant percentage of the borrowing when compared to the FDIC data above.  While this data is hard to verify, given the size and growth of these companies it is clear that their importance will grow and become a serious source of capital for small to medium size businesses.  

In addition to the companies we’ve mentioned, we are also seeing many new offerings from established companies such as Amazon, Square, and Paypal, jumping in to finance their small clients and further validating the size and attractiveness of this asset class.  These companies see the void that needs to be filled and the advantage they have due to the information they collect on the firms using their products.    There are also companies devoted to assisting a business owner in finding the right loan from non-bank lenders, such as Fundera, Lendio, and Biz2Credit.

Many of these online loan originators were funding all or most of the issued loans with bank credit facilities, focusing their technological expertise on the borrower acquisition and underwriting segments of their business model. Orchard is excited about the expansion many are making to the marketplace lending model.  This structure opens up the potential for borrowers to access various types of investors who may have different investment goals than those of a traditional bank.  As long as banks are the only funding source for loans, only those borrowers that meet the criteria necessary for a bank’s business model will be funded.  The ascent of marketplace lending unlocks the possibility of various capital sources, and therefore various business models, to engage in the funding of loans for all purposes – including business growth.  Orchard is excited to be playing a role in this innovative and exciting new time in financial history, enabling the democratization of credit to a wider range of borrowers.

The Price of Credit - Interest Rates Over Time

A core aspect of any lending-related industry is the price of credit.  As marketplace lending has grown and matured since its inception, interest rates for borrowers have moved along with economic conditions and the supply of investor capital. In today’s analysis, we will explore the rates seen across the borrower spectrum on the major online marketplaces and compare them to other major consumer asset classes.

Average Borrower Rates Over Time

In the chart below, we show the mean borrower interest rate over time for LendingClub and Prosper.  Interestingly, these 2 originators have had a significant gap in averages for most of their lifetime, though the lines have recently converged.

Of course, simple averages never tell the whole story.  Each platform offers loans across a broad range of interest rates, and it behooves us to look at the full distribution.  In the chart below, we show a boxplot of interest rates, by originator, for each month of originations.  Since 2009, the lower bounds seem to be relatively similar for both originators, but the upper bounds are quite different.  Prosper offers some loans at interest rates well above those of LendingClub, thus bringing up their average.

To get a closer look at what is happening in the data, let’s take a look at interest rate distributions for distinct periods of time.  The charts below show the distribution of loans made by interest rate band for January 2013 and 2014 respectively.  While Prosper has maintained a presence in the higher interest rates, it has now shifted its distribution toward lower-priced loans.  LendingClub’s distribution has been rather consistent.

Context – National Consumer Credit

The table below is taken directly from the U.S. Federal Reserve website’s August 2014 release.

Interestingly, while these rates have changed over time, they have not fluctuated with the same order of magnitude we have seen on the marketplace lending originators.  This is perhaps an indication that interest rates for marketplace lending have shifted not solely because of the overall economic climate but also due to the rapidly changing nature of a nascent industry and the dynamics of borrowers and investors. As the industry matures, there is a possibility that we will see the same convergence and stability experienced in more traditional forms of lending.

July 2014 Marketplace Lending Index Returns

Month and Year-to-Date Asset Class Returns

As seen in our previous monthly marketplace lending recap, we will continue to benchmark the Orchard US Consumer Marketplace Lending Index against comparable US Fixed Income asset classes.  This will help both old and new investors in understanding their returns.  

The Orchard US Consumer Marketplace Lending Index continues to outperform many of the comparable US Fixed-Income asset classes on both a month-to-date and year-to date basis.  

Source: Fixed-income asset class returns based on Barclays Benchmark Indices

Source: Fixed-income asset class returns based on Barclays Benchmark Indices

Source: Fixed-income asset class returns based on Barclays Benchmark Indices

Source: Fixed-income asset class returns based on Barclays Benchmark Indices

European Platform Analysis: Bondora & Disposable Income

In March of this year, we discovered a European originator with publicly available data called isePankur and wrote a blog post based on that data.  In April, isePankur raised a significant round of capital and renamed itself Bondora.  Since our initial post, we have followed Bondora closely, been impressed with their growth, and admire their openness with data.  Similar to Prosper and Lending Club, Bondora publishes loan data on its website, allowing prospective investors (and the general public) to delve into the borrower attributes and performance of the loans on the platform.  We believe this transparency is great for the investment community.  Marketplace lending works because investors can make informed decisions about the types of loans that make sense for a given investment strategy. This can only be done effectively if there is data available to analyze. 

Given the richness of Bondora’s data, it is possible to run a multitude of analyses on the demographics and performance of loans on the platform.  In fact, Bondora collects certain borrower attributes (e.g. gender & martial status) that are never found on loan applications in the US.  While these are interesting, we felt it would be more relevant for our readership to compare an analysis that we've performed on Prosper and/or Lending Club with Bondora – we will use the disposable income analysis from March. 

First, we’ll take a look at the debt amount provided in the data.  This represents the debt payments the borrower is already committed to making each month prior to applying for this loan.  We see that the payment ranges from ~€200 to ~€650.  The number seems to have increased over time, which (from the lower graph) appears to be from introducing the new geographies (Finland, in particular).

Next, we look at the annual income distribution.  Based on researching the data, the income provided is monthly.  Once annualized, we see that the average income for borrowers on Bondora is around ~€15K.

Diving deeper into the distribution, we look at it by country and credit grade.  This gives us a bit more insight on the income distribution and how Bondora assigns credit groups (analogous to Prosper and Lending Club’s credit grades).  Finland appears to have higher income cutoffs for entry onto the platform.  It is also clear that income is an input into assignment of credit group.

Now that we have an understanding of the monthly debt and income of the borrowers, we can analyze the monthly disposable income.  Bondora calculates this in the same way we did when we analyzed this for Prosper - taking the monthly income and subtracting the monthly debt payments.  Below is the distribution.

The distribution of disposable income by country and credit group shows a more distinct picture than the monthly income distribution.  Disposable income is clearly a large driver to determining credit group.

Next, we look at the default rates by disposable income band.  Unlike Prosper, we do not see the same clear pattern when assessing the default rates (in this case defined as 30+ days past due) versus monthly disposable income.  Monthly disposable income, as calculated here, does not appear to impact the default rate.  This could be because disposable income is such a large factor in underwriting and pricing (as seen in above graphs) that it no longer provides any further insight in analyzing the loans once they are on the platform and funded by investors.

In conclusion, when we did this analysis on Prosper’s data, it was clear that monthly disposable income was a predictor of risk on those loans.  As the disposable income increases, the likelihood of default decreases.  This makes sense, as it would be easier for a borrower with more money every month to make a payment on time.  With Bondora, we don’t see the same pattern.  There are many possible reasons for this, including that Bondora clearly uses this metric in their decision making.  It is possible that the loans that Bondora chooses to make available to investors from borrowers with lower monthly disposable income have passed other credit criteria that make them lower risk in other ways.  Given the richness of Bondora’s data, we will continue to review it and write about it in future posts to answer these questions and others.