Bondora Investments Using Decision Trees – Review of Progress – Part 5

This is part 5 of a series of guest posts by British Bondora p2p lending investor ‘ParisinGOC’. Please read part 1, part 2,  part 3 and part 4 first.

The Management of Change

As mentioned in my earlier article on the construction of the decision Trees, my responsibilities when employed (yes, dear reader, I am now retired) included the successful proposal to create new teams to conduct Data Mining and produce and disseminate Metrics relating to the research activities. As on many other occasions, I was then charged with making my assertions real by staffing and then running said teams to realise the benefits I had stated should arise.

As part of my (rapid) learning in these activities, I came to understand the need to maintain processes until solid analysis could isolate and support changes. So in this review period, for those elements under my control, I have maintained certain actions within set parameters until I felt I could justify a change and then have maintained that changed process until the next time the data supported a further change.

Changes I Controlled

Given that my need to change my selection process was as a direct of seeing my money rapidly disappear (!) I limited my ongoing expenditure to the minimum purchase (5 Euros) allowed by Bondora and only made 1 purchase per selected Loan Application.

This continued throughout October 2014, when I felt that the downward trend in parts falling behind with payments was established and likely to continue. From the beginning of November 2014 onwards I increased the number of parts of any single loan application I would buy to 2, still of 5 Euros each. Note that for some application types with, for example, a higher (between 5% to 7%) indicated historical failure rate, or a very high (above 45%) interest rate; I still limited my purchasing to 1 part of 5 Euros.

This Purchasing policy remained in place until the beginning of April 2015 when my increasing confidence in the selection process, my increasing cash reserve and other factors described below, meant I felt able to increase the value of purchases (to include 10 Euro parts if I felt an application was sufficiently strong) and increased the number parts purchased of any particular loan. This latter element in particular allowed me to take advantage of events outside of my control that offered opportunities that had not previously existed, explained later in this article.

Errors in my Process
In the period October 2014 to the end of the year, I was updating the Trees twice a month. There was no detailed timetable, but the Trees did exhibit a greater degree of change in this time than was later the case. It was during the first update in December, week 51 of 2014, I noticed that the previous Tree had been built using corrupted data. It was only later in the review period that I noticed that this period – from weeks 48 to 50 inclusive – exhibited the last “spike” in defaults.

From the next update onwards (31st December 2014) I implemented a more rigorous update procedure and restricted the updates to 1 at the end of each month. I felt that this may enable changes in the Tree Structures to be more visible and so attract my attention to these changes and validate the process that had generate them, thus avoiding process errors. The fact that the datasets provided by Bondora were subject change without notice (and did so often) was an additional factor in the decision to have fewer, more rigorous build events.

I worried that fewer updates to the Trees would lead to out-of-date trees and more In Debt and Defaulting loan parts, but this has not become apparent either in daily use or this review process.
I have noticed that the Decision Trees are not static and do change over time. Sometimes – rarely – these changes occur at a high level and are very noticeable. However, the Trees have changed in a subtle way at lower, more compartmentalised levels. This is discussed later in this article.

Changes I could not Control

Whilst I have tried to maintain a tight control over my activity since starting to use the Decision Trees to guide my loan selection, there is the overall Bondora environment over which I have no control. As noted in the previous article (see part 1-3), Bondora is a dynamic environment and changes, whilst usually signalled in advance, cannot usually be planned for and just have to be accommodated when the reality of the change becomes apparent. Where possible I have noted the changes that have occurred. As part of this review, I have gone back over the last 9 months activity to try and relate these changes and how I believe they have, or may have, affected my results.

Portfolio Manager
The Portfolio Manager in place up to the end of 2014 was an automated, parameter-driven mechanism to allow investors to automatically invest in loans that meet the criteria set by the investor. From the start of 2015, Bondora made major changes to the Portfolio Manager, preceded by allocating a “Risk Segment” (running from low to high risk) to each Loan Application.

Whilst a Loan Application retained the previous Credit Score and associated Credit Group (essentially an income-related grading), these no longer played a part in the new Portfolio Manager, which no longer allowed Loan Selection by any criteria other than the new “Risk Segment”. Probably the most contentious element of the new Portfolio Manager was the loss of selection by Country. The use of Country was a critical element in the previous automated selection process for most ( if not all) investors, and its loss was not well received on the official forum.

In terms of my process of Decision Tree analysis, this changed nothing. All the previous data was still present and some new data was added about the New Risk Segment and the process associated with it. I have considered adding the new Risk Segment data to the Decision Tree analysis, but decided against this primarily as its introduction, occurring as it did some 3 months into my experiment, had the potential to dramatically alter the structure of the Decision Trees, creating a possible disconnect at this point.

A secondary reason in my decision was the fact that this data was itself the result of an analysis conducted by Bondora and for which there is no detailed discussion or publication showing how it has been arrived at. Whilst I am not surprised at the decision not to publish what is, after all, company confidential data, the output – a legend consisting of a 1- or 2-letter classification – is not an independently verifiable fact, it is merely the output from an analysis and shares this feature with my own Decision Trees.

The major difference between this and the Decision Tree output I have is the context that is provided by a full Decision Tree to those who wish to use it. IMHO, the discerning viewer can decide from the context of a complete Decision Tree whether the end point of a particular branching of the tree indeed describes a trend or is just a convenient mathematical activity that segregates the data, but reveals no trend. I offer the snapshot of Self Employment from the Decision Tree for Estonia as an example of this added value.

Decision Tree View Estonia Bondora

 

To me, the bigger picture describes a trend suggesting that the longer the applicant has been in the same employment, the less likely a default will occur. It also shows that the Decision Tree has found that those in the same employment for over 5 years can be further segregated by age, with all defaults occurring in a single age range (45 to 51). Furthermore, the sample size of the >5 years employment is 51 and the defaults, which all occur in the noted age group, amount to just 2 examples – a 4% default rate on the set of 51 as a whole. Is this further segregation a guide to investment or just a “Clump” in a larger data set? In the words of the immortal Clint Eastwood “You’ve gotta ask yourself one question: “Do I feel lucky?Well, do ya, punk?.

Application Process

In last half of February 2015, Bondora introduced changes to the application process designed to allow applications to be assessed by Investors before all data had been collected and, where applicable, validated.

This had no immediate effect on the Decision Tree analysis, but did require minor amendments to the process. Many applications were taking up to 5 or even 6 attempts before they became fully acceptable and finally funded. Many of these rejections took place after funding was in place. They were then cancelled and re-submitted with updated data. It was important that such applications did not get counted as “Previous Applications”. This field does appear in some lower levels in a Decision Tree and therefore new data cleaning activities (explained in the previous article) had to be introduced into the process.

Server Capacity Issues at Bondora

Around the 2nd week in March, 2015, the servers at Bondora ran into capacity issues. This affected both the ability of the applicant to apply for loans and for investors to lend.

Aggregated effect of Bondora changes

Concurrent with the introduction of the changed application process and the server capacity problems, it is apparent from a chart provided by Peerlan that the new Portfolio Manager’s ability to fund loans collapsed, effectively to zero.

Portfolio Manager Funding from Peerlan - 2015-06-23 snapshot

When Bondora fixed their capacity problems, the mix of Loan Applications becoming available to manual investors had changed dramatically. Whilst this had no effect on the use of Decision Trees to select loans, it meant that many more loans became available to manual bidders. Many of these loans were Estonian, historically considered to be of higher quality.

This availability of more loans of potentially higher quality is reflected in my activity by the highest level of loan part purchases seen since the start of my use of Decision Trees. This higher number of purchases occurred even with the restrictions I had placed on myself regarding the level of purchases per Loan Application, mentioned earlier.

As I write this review, the new Portfolio Manager process has again changed, this time to run more often, with a target of running effectively all the time. This new process appears to have a dramatic effect during the 16th July, reducing opportunities for manual bidding on new Loan Applications essentially to zero, as the new Portfolio Manager process swept up all new listings.

New Loan Applications have appeared again the next day and a close reading of the Bondora “Guide to Investing” FAQ suggests that Loans that fail to be filled immediately should appear out of the back of the new process and become available to manual investing and this appears to be the case. This occurrence and the availability of loans on the Secondary Market (at a premium in most cases), leaves me feeling that my work to date has not been in vain. Time will tell!

Flip forward to the final part 6.

Bondora Investments Using Decision Trees – Review of Progress – Part 4

This is part 4 of a series of guest posts by British Bondora p2p lending investor ‘ParisinGOC’. In part 1, part 2 and part 3 published in December 2014 you could read how he used the data to built decision trees to identify lending opportunities. Now you can read how that strategy worked out.

Introduction

In August 2014, I realised my portfolio of P2P loans at Bondora was not performing as I would wish. There was an urgent need to change the way I selected loans in which to invest the money I had at my disposal. My search for a better way of selecting loans lead me to use Decision Trees to analyse the loan data available from Bondora using “RapidMiner” – software available to download for free.

It is now over 6 months since I described my original work to construct the Trees. This follow-up article chronicles what I believe is the success of my efforts to date whilst also describing the multiple factors, both within and beyond my control, that mean that, whilst I feel very comfortable with the progress made to date, others may feel that I have just been lucky!

The journey since I created my first Decision Tree and started to make purchasing decisions based almost totally on their outputs has been one of constant change. Detailing the changes to elements over which I have no control has shown me how they contribute to what I believe is success as much as my own efforts to improve the selection processes. Describing the change in the Decision Trees as well as their use in the dynamic Bondora environment has left me feeling that, without constant monitoring and review of both the process of creating the Trees as well as their use, it may still be very easy to snatch defeat from the jaws of victory.

Key to ensuring the veracity of my protestations of success has been the maintenance of a consistent approach to my selection and lending process. To this end, I will describe those changes to my process that I can control and explain how and why such changes have taken place. In short, I have maintained a restricted buying policy, investing only the minimum amount (5 Euros) at any one time and, latterly, only buying a maximum of 2 loan parts (of 5 Euros each) in any one loan, depending on the outputs from the Decision Trees and my own mood at the moment of purchase.
I realise that this last phrase is not at all scientific, but the fact that my Portfolio of c.12000 Euros was not performing as expected was for me, a non-trivial affair and some emotional response has to be accommodated.

I have already stated that I believe my efforts have been successful. This is based on the fact that the rate of default (Once a loan principal has been overdue for 60+ days, it is labelled as “defaulted” – Bondora FAQ) in my portfolio has returned to historical, pre-2014 levels. Up to this time, even though I had come to realise that I needed to actively manage my portfolio, my selection of loans was done almost entirely using the “Portfolio Manager” – an automated, parameter-driven purchasing function provided by Bondora and supplemented by instinctual analysis of the descriptions of the Loan Applications available to invest in.

Simple Chart - Held Loans and Defaults

 

Looking at the simple chart of Held Parts/Defaults, the number of defaults in held loans rose significantly over the summer of 2014, coinciding with a big increase in both the number and value of investments on my part. Referring to the same chart, it can be seen that, even though the number of investments remains close to summer 2014 levels, my defaults have fallen to the numbers experienced earlier, at much lower volumes.

With my new-found confidence that I have a process for selection and management that appears to be sound, I have started to increase the volume of Loan Parts purchased so that the value is now approaching Summer 2014 levels of investment.

Progress to date

Graphical representation of Progress

I will use a more detailed graph showing the volume of Loan Parts purchased, those subsequently sold, those “Overdue” and those in default (still held by me as well as sold) to hopefully illustrate the performance of my selection and management processes. Continue reading

One Year Invested in Zencap

This is a guest post by German investor Martin R.. The article was written in April.

These days, Zencap celebrates its first anniversary. I’ve been involved right from the beginning and invested the full 10k€ you can invest without having a premium account.

Zencap – my characteristics

Zencap offers investment in corporate loans. You invest 100 EUR in one loan. The total loan is usually between some 10,000 EUR and approximately 200,000€. There are different scoring classes essentially determining the interest rates which are usually located between 5% and a little over 10%. The loan term ranges from 3 months up to 5 years, the main focus being 3 years. As the loans are instalment loans, you will usually have half of your investment plus interests available after 18 months. The nominal interest rates are decreased by 1% through fees for the investor. The loan listings are presented with a short description and have differently detailed documents attached. Some projects have personal sureties.

My experiences

are mixed. I’m rather satisfied with a yield of about 5.7% and no payment delays up to now. The payout takes place promptly after the scheduled payment at the 15th of each month. The bidding amounts are straightforwardly drawn through direct debit, however, the period between bidding and drawdown drag on very long from time to time (debiting is just before the first paying out, though). Now and then there are special promotions which increase the yield (see below). Continue reading

How I Explored P2P Lending – My Review Part II

This is part II of a guest post by British investor ‘GSV3Miac’. Read part I first.

Most of my concerns about P2P lending revolve around its relative immaturity. Even ZOPA, the oldest in the UK, has only been around 10 year or so, and have changed ‘just about everything’ at least twice. Funding Circle (“FC”)have 3-4 years history, but there have been no two years where the business has actually been stable (maximum loan sizes, loan terms, Institutional participation, etc. have all changed pretty much continually over the period I’ve been investing). How well the companies, and their borrowers, would survive a real recession, can only be guessed at.

What do I actually invest in? Well practically anything if the rate looks good. My ‘core holding’ is in RS, but there is nearly as much spread across the P2B platforms. For extra P2P related risk (and maybe reward) I also signed up to invest in the Assetz and Commuter Club capital raises (via SEEDRS). With EIS investments some of the money at risk is renated tax, which you had a 100% certainty of losing to the government anyway.

I do not plan to hold most of my investments (particularly in FC) for the full 5 years. After a few months the financial data is well out of date (much of it is already out of date when the loan is approved!) and unless you want to spend time checking how the company is doing, it is easier to sell the loans on and start anew.

Similarly if rates start to move dramatically, it’s time to ‘flip’ or ‘churn’ .. selling a 7% loan part when rates move to 9% is possible, but might sting a bit. Selling a 7% loan part when rates have moved to 14% is going to hurt a lot, or might be completely impossible. If rates move the other way, selling a 7% loan part when average rates are 6% is not only easy, it may be profitable (assuming the platform allows marking up). You might wind up with un-invested funds, but as someone succinctly put it on the P2P forum, ‘un-invested is a lot less painful than lost’.

The future looks equally interesting .. we are promised P2P investments within an ISA (do NOT hold your breath, this seems to be moving at a glacial pace so far), which could result in a ‘wall of money’ arriving on the scene. We are promised P2P losses to be tax deductible (against income, rather than capital gains), which has an impact on the worth of a protection fund. We will inevitably see some new entrants appear as the P2P area grows and become more attractive (Hargreaves Lansdown, a very large fund management player, has already indicated they might get involved, I believe). We will equally inevitably see some more of the current players merge or vanish, and many of the loans default.

As I may have mentioned a couple of times, nothing has been very stable so far .. most of the platforms are still ‘feeling their way’ with immature software (this is polite-speak for ‘bugs’), and business models/systems which are still evolving. The basic P2P premise of connecting people with money with people who want it, without too much activity in the middle, does not appear to scale too well when the number of each side get big (a million people bidding to fund a thousand loans each day is not something to contemplate lightly). Platforms need to grow to survive and they need to grow in balance – if they double the number of lenders, they need twice as many willing borrowers, and vice versa .. Asymmetrical growth just annoys whoever is on the surplus side, distorts the rates, and results in no growth at all – you need both a lender and a borrower to have any business. It is obvious, but very hard to manage. Continue reading

How I Explored P2P Lending – My Review Part I

This is part I of a guest post by British investor ‘GSV3Miac’.

About the author.. I spent 25 or so years in software engineering, programming everything from IBM mainframes to microchips in early Hotpoint washing machines. I must have been halfway competent (or not) since I wound up managing a software development group, a large IBM computer centre, workstations of networks and PCs. When my (American owned) factory shut down I spent the last year (in between managing the closure) retraining as an IFA. I qualified, but I never actually practised – I took my redundancy / pension and headed for the hills (of Shropshire). That was a while ago, so don’t expect me to know chapter and verse on the latest tax wrinkles! *grin*

How did I get into P2P (misnamed .. it’s largely P2B these days .. much of is headed for B2B!) lending? Blame my mother .. she died, and left me a sum of money which was not expected, and not really critical to my future. Having no children (there being, IMO, no people shortage on the planet) it is probably all headed for charities one day, so I thought I might as well have some fun with it. Before I did that, I had, of course, gone through the approved checklist .. i.e.

‘Emergency’ easy access cash account(s) .. tick.

Pay off the mortgage .. tick.

ISA(s) .. tick

Pension Provisions .. tick

Stock market investments / bonds / shares / funds ..tick

OK, anything left can be risked a bit. (I accept that stocks and shares and even cash has =some= risk attached, but now we are looking at ‘high wire with no net’ type options .. VCTs, EIS schemes, and yep .. P2P lending). If you want to plan for ultimate disaster (Ebola pandemic, nuclear war and global financial meltdown) then probably investing in long dated canned food, and an underground shelter on an island upwind from everywhere, is your best bet. More modest (and likely) risks can be mitigated by spreading your investments around a lot, and by being conservative in your assumptions of what you might get back.

I started my P2P journey (in 2013) with Funding Circle (henceforth ‘FC’) and ZOPA, both of which I had heard about from a friend, and I dipped my toes in rather gingerly at first. ZOPA had been going for some time, and I probably missed their best years (when you could decide who to lend to, and later when you could at least still decide at what rate you’d lend). ZOPA had just introduced their ‘safeguarded’ lending, and started fixing the rates, so even their name (‘Zone Of Possible Agreement’) no longer made sense. I stopped lending with them after less than 6 months .. the rates were just not attractive (and unpredictably so). On the plus side, the exit from ZOPA was fairly cheap and painless.

As an alternative to ZOPA I went to look at Ratesetter (RS), which still lets you set the rate(s) you are willing to lend at over 1,3 or 5 years (or monthly). No control over who gets it, but at least some control over what they pay; and (like modern ZOPA) there is a provision fund which should hopefully protect you from bad debts. Exit from RS can be quite expensive though, so best to lend for no longer than you are sure you can do without the money for. Basically they charge you the difference between the rate you would have got for the actual period you lent for, and the rate you got by lending for a longer period. I still like them, for simplicity with just enough control to make it interesting, and I lend / recycle in the 3 and 5 year markets depending on the rates at the time (typically I expect at least an extra 1% for signing up for the extra 2 years). Continue reading

How I Selected My Preferred P2P Lending Marketplaces – Part II

This is part II of a guest post by British investor ‘Pete’. Read part I first.

The number P2P / P2B platforms in the UK has increased quite quickly over the past few years and I have currently settled on 3 further UK platforms that suit my needs and I strongly believe will be with us long term. In saying this I am not in possession of any privileged information and I am not by inference making any adverse comment about other platforms.

In alphabetical order

Ablrate

One of the new platforms (launched July 2014) that I have chosen to invest in and so far I have had a very positive experience. Specialising in secured Aircraft leasing and Plant and Machinery I have had the chance to diversify into a market that I knew little about before I started on my ‘due diligence’. The market may be new to me but there is a wealth of responsive experience behind Ablrate and coupled with a website update and promised increasing flow of loans I anticipate that my exposure with Ablrate will continue to grow. One interesting ‘innovation’ available on certain loans is ‘Instant Returns’. With long draw down times on some loans the potential for ‘dead money’ is large, instant returns circumvents this issue.

Assetz Capital

I have been investing with Assetz Capital since the second quarter of 2013 and have built up a diversified £ five digit portfolio of secured loans which continues to grow1. As with Ablrate there is a good, responsive and experienced team behind the web site, something that has become more than apparent when dealing with the occasional distressed loans that we must all expect when investing. Assetz Capital have big plans for expansion (they have already grown considerably since I started investing) and a relatively recent change to the way loan parts are bought has removed a very large percentage of the ‘dead money’ scenario that many of us early adopters experienced, not universally liked, I for one view it as a very positive move that has helped to push up my return on investment. I look forward to new opportunities this year.

1 I do not invest by choice in the provision fund protected ‘Green Energy Income Account’ preferring to take on the risk in return for a slightly higher returns.

Wellesley & Co

Again I was one of the early adopters and took advantage of some very attractive introductory rates that were offered. The loan and repayment terms suited my needs perfectly for tax planning purposes. Since then the rates have unsurprisingly been lowered and whilst Wellesley & Co have expanded rapidly and their range of investments on offer has expanded I find myself already invested in those areas with other platforms so I am running full term with my current investments whilst keeping an eye open on what is on offer.

Bondora

I also invest in one non UK platform, Bondora. This would probably be regarded as the ‘odd one out’ in my list of platforms. Far more volatile than the other platforms that I invest in Bondora has expanded rapidly since I started investing in the second quarter of 2013. I have experienced several changes to the platform, some which I have liked and several that I have not. I have experienced new markets being opened up and some eye watering rates of default in these new markets. That said and in spite of the treatment of defaults by the UK tax man and the strengthening of the Pound against the Euro (@16% since I started investing) my return after tax has remained positive. I spend more time on this relatively small percentage of my total investments to keep the returns positive than I do on any of the others. Continue reading