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Post by stevefindlay on Aug 12, 2017 7:45:47 GMT
Returning to the subject (this thread is supposed to be about speed of lending; cash drag - not rate of return). Something is very very amiss here indeed! My investment rate is just completely different to what I should have received according to the last graph posted by stevefindlay above. I do not mean at slight variance with, I mean completely, utterly, totally different! - and not in a good way. What the heck is going on? I will have a look at my data in detail and post back. Happy to take a look at your account and investment settings if you want to send you details to invest@bondmason.com Please note, though, I'm away next week so my response time may be a little slower than usual.
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gnasher
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Post by gnasher on Aug 12, 2017 8:16:05 GMT
I sent a spreadsheet with my calculations to invest@bondmason.com yesterday before I saw you latest graph, I look forward to a reply.
In headline terms I first invested on 15th March, I have added more funds in several stages resulting in the current £24K.
I have 6 investment periods with different capital on the platform. Looking at each period and the amount invested during the period I calculate time to be fully deployed as follows :
48
128
52
71
80
225 (but only a short period so perhaps not valid)
I calculate a weighted average time to full deployment on my portfolio to be 90days and this during a period when according to your graph I should be getting deployed in 30 days or so.
Edit : 90 days is wrong - see my later posting on 25/8
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Post by stevefindlay on Aug 12, 2017 20:28:07 GMT
I sent a spreadsheet with my calculations to invest@bondmason.com yesterday before I saw you latest graph, I look forward to a reply. In headline terms I first invested on 15th March, I have added more funds in several stages resulting in the current £24K. I have 6 investment periods with different capital on the platform. Looking at each period and the amount invested during the period I calculate time to be fully deployed as follows : 48 128 52 71 80 225 (but only a short period so perhaps not valid) I calculate a weighted average time to full deployment on my portfolio to be 90days and this during a period when according to your graph I should be getting deployed in 30 days or so.You have my spreadsheet with my calculations. As I say something is very wrong somewhere. Please can you resend, or send to my personal email address: stephen.findlay@bondmason.com I can't see your email in the invest@bondmason.com inbox. Happy (and interested) to take a look. Many thanks, Steve
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gnasher
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Post by gnasher on Aug 14, 2017 3:08:51 GMT
OK spreadsheet calculating my weighted average time to full deployment of 90 days resent to invest@bondmason.com and to stevefindlay. If anyone else is interested here is my graph :  |
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jimc99
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Post by jimc99 on Aug 14, 2017 5:05:28 GMT
Cannot see a problem with your graph, looks just like mine.
You do realise that it's virtually impossible to be 100% invested ... ever? Loans will be being repaid regularly and not reinvested immediately so I expect up to 3 or 4% of my capital to always be uninvested...
Happy with BM so far. Around 8.5% gross return forecast.
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gnasher
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Post by gnasher on Aug 17, 2017 1:52:30 GMT
Cannot see a problem with your graph, looks just like mine. You do realise that it's virtually impossible to be 100% invested ... ever? Loans will be being repaid regularly and not reinvested immediately so I expect up to 3 or 4% of my capital to always be uninvested... Happy with BM so far. Around 8.5% gross return forecast. I am glad that you are happy with BM, but I do not think that you have understood the point in question. It is rate of investment, not the achieving of 100%. I too would be very happy if I was 90%+ invested within an average of 30 days or so as advised on the BM website, and which I should have achieved according to the graph posted by SF above for the period that I have been using BM. However my rate of investment is consistently much worse than that. The issue is the slope of blue line, not that it never touches the black one. SF is on holiday at the moment but I have been in e-mail contact with him and he will be doing a review of this on his return. So for those of us who are not happy perhaps we may hear something before too long.
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Post by stevefindlay on Aug 17, 2017 16:54:32 GMT
I've posted the reply to gnasher here (as well as by email) to continue the thread. [gnasher - if you would like me to take any of this down as it relates to your private portfolio, then please just ask]
The analysis in the image seeks to show how long it took for each deposit to be fully invested (in isolation from earlier or later deposits). To do this, I’ve used the invested amount as at the date of each deposit, to set the target amount for full deployment for that deposit, and then looked to see when @gnashers portfolio first hit that level of deployment. It shows that the average number of days for each deposit to be deployed is 32 days.  I’ve not looked at the total balance each time, as this “carries forward” any slower deployment times relating to earlier deposits. It is difficult to make this a clean analysis for each deposit, as the rate of deployment for later deposits will be slowed by repayments on loans from earlier deposits. But I think the analysis is a fair reflection of the deployment rates. A couple of general observations: - Rate of deployment feels like our biggest (last major) issue to solve: it is something we work hard at, but I recognise we would like to do better
- We will always prioritise loan quality over rate of deployment: we would rather see clients to be slower to be allocated than see an increase in defaults from lower loan quality
- We are well aligned: aside from wanting to see all clients do well; we only receive a fee on invested capital, so if your funds aren’t invested we aren’t earning anything
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gnasher
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Post by gnasher on Aug 18, 2017 18:01:50 GMT
I have no problem with this data being on this site, however I do have problems with the way that my average deployment time has been calculated as 32 days, as opposed to my 90. Yes we are talking apples and oranges ....., chalk and cheese ...... ( but not going so far as to mention that old saying about statistics). I will think about this a bit more when I have the time and perhaps post a detailed analysis of the 2 methods used, so everyone can judge which is a fairer reflection
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TheDriver
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Slightly bonkers
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Post by TheDriver on Aug 20, 2017 7:27:29 GMT
OK spreadsheet calculating my weighted average time to full deployment of 90 days resent to invest@bondmason.com and to stevefindlay . If anyone else is interested here is my graph : TBH, although I have questioned the deployment time claimed by the platform, I think your analysis looks unrepresentative of your graph, which seems to show much better investment times than you have calculated, although deployment time for your INITIAL deposit looks similar to mine which is my point of difference with the expectation created by the platform! Timescales generally seem to improve with each additional deposit giving an average close to that claimed by BM. This would be expected if the investment %age remained the same, because loan purchases would be larger - and can only be reduced once anyway with the current options, limiting this influence.
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gnasher
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Post by gnasher on Aug 21, 2017 4:32:19 GMT
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Post by stevefindlay on Aug 21, 2017 14:03:04 GMT
Following on from the chart above (showing the average deployment time of 30.2 days)...
The shape of the distribution around the average of 30.2 days probably gives rise to many of the issues noted on this forum relating to deployment periods. The average is 30.2 days (as we know from above. Clients (quite rightly) should be able to expect something close to the average (mean or median). However, the distribution is as follows:
• The first quartile is 7.2 days: so 25% of deposits have been fully allocated in a week
• The second quartile (median) is 20.6 days: so half of deposits are fully allocated within 3 weeks or less
• The third quartile is 42 days: so 75% of deposits are fully allocated within 6 weeks or less.
• Therefore 25% of deposits have taken more than 42 days to be allocated.
And this is the problem.
Clients may mistake the average of 30 days as being an upper bound, or expect this average to be hit in 100% of cases. But this isn't the case - the distribution of deployment times is more varied than this.
So, whilst some clients may be very pleased with a much shorter deployment time for deposits (less than one week), we have just as many deposits requiring more than 6 weeks to be fully allocated.
The allocation process itself is fair across all deposits (and clients), therefore the main determinant of allocation speed is simply the ebb and flow of funds vs. opportunities over time.
Nonetheless, we will now consider ways to make deployment rates closer to the average in all cases, as this will be likely to improve client experience.
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TheDriver
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Post by TheDriver on Aug 23, 2017 5:34:57 GMT
It seems this thread has finally identified the discontinuity between the platform statement of "Initial deposits may take an average of 28 days to be fully deployed . . . . " and the experiences posted here.
It appears deployment period is in fact calculated as the average time for ALL deposits, which are inherently quicker with subsequent tranches due to the potentially increased size of allocations. Therefore I contend that the headline statement DOES set an erroneous expectation for initial investments! which will tend to be in the fourth quartile above, ie. take more than 42 days.
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Post by Deleted on Aug 23, 2017 8:18:51 GMT
This thread is starting to help understand the cash drag which is good.
I'm curious: in the average figures, is that averaged across all client accounts whether at 1% or 2% diversification? That could make it much harder to get a clear picture for each client.
Also, is the difference in allocation time for an initial investment solely due to availability of investments at and shortly after (e.g. 1-2 months) the time of investment?
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Post by stevefindlay on Aug 23, 2017 16:19:59 GMT
This thread is starting to help understand the cash drag which is good. I'm curious: in the average figures, is that averaged across all client accounts whether at 1% or 2% diversification? That could make it much harder to get a clear picture for each client. Also, is the difference in allocation time for an initial investment solely due to availability of investments at and shortly after (e.g. 1-2 months) the time of investment? (1) Average figures in this thread are across all clients - 1% and 2% concentrations. (Our stated target average of 28 days is just for 2% clients) (2) Difference in speed: yes, the time taken for the next 50 loans (or so) to hit the platform; and (although less important) the overall demand from new clients. Volume of loans, rather than value, tends to be the issue. For example: investing £5-10M a month isn't an issue; finding 50 good loans (of decent size) in a month is the challenge.
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Post by stevefindlay on Aug 23, 2017 16:49:21 GMT
It seems this thread has finally identified the discontinuity between the platform statement of "Initial deposits may take an average of 28 days to be fully deployed . . . . " and the experiences posted here.
It appears deployment period is in fact calculated as the average time for ALL deposits, which are inherently quicker with subsequent tranches due to the potentially increased size of allocations. Therefore I contend that the headline statement DOES set an erroneous expectation for initial investments! which will tend to be in the fourth quartile above, ie. take more than 42 days. The full statement is "Initial deposits may take an average of 28 days for clients with a 2% setting"; which is valid over the course over the last 18 months; although we would like to beat this in the future. Your observation that initial deposits take longer is true, but not significantly so: - the average for all initial deposits (for clients with either 1% setting or 2% setting) is 36.8 days; - the average for all deposits (for client with either 1% or 2% setting) which, as we know from above, is 30.2 days. I maintain that the issue for client experiences is the distribution of deployment times around the average (as noted above); not any inaccuracy in the average itself - either how it is calculated or referenced.
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