When do they come online for individual investors (assuming institutional investors don't want them)?
After about 12-hr:
"
a randomized subset of loans by grade will be available to purchase as a whole loan (i.e. not in $25 increments) only for a brief time period (12 hours), while all other loans will be immediately available for fractional purchase. If the loans are not purchased as whole loans in the specified time period, they will become available for purchase in the standard, fractional manner."(
http://blog.lendingclub.com/tag/whole-loans/)
Well wouldn't we want that disclosed...that the loan failed to sell as a whole loan?
Just did a quick custom filter on IR...the results are counter intuitive.
No I meant disclose whether one kind has a worse track record. I filtered loans from Jan 2012 to today, grades D through G. Initial fractional loans had 6.2% loss. Initial whole loans with 10 or more lenders had 3.5% loss (I presume these to be whole loans that institutional folks didn't buy). Initial whole loans with fewer than 10 lenders had 2.9% loss. Baseline loss for all loans meeting those criteria was 5.7%
Keep in mind that those results are skewed due to the immaturity of the bulk of whole loans. The whole loan program began late September/early October of 2012.
I agree, I ran that analysis on my phone on the fly just to see. I'll narrow to sept 2012 when I'm home.
I'll have a guest post on the whole loan program on the blog tomorrow.
Sorry team, to clean this up. Running Sept-12 through today D-G notes, I see the following:
Fractional first: 3.9%
Whole (10 or more lenders): 3.5%
Whole (less than 10 lenders): 2.9%
Baseline loss: 3.8%
My point here maybe isn't to prove this to a mathematical certainty, but, if I understand the whole loan program correctly, it seems that we can show sum degree of funneling. Put another way, I'm seeing an issue from a securities regulation point of view that they don't disclose that the poor quality Grade [X] notes are offered to the public as compared to the equally graded notes offered to preferred customers.
Maybe the whole loans that actually got bought as whole loans had a higher default rate, such that the total whole loan pool was roughly equivalent to the fractional first pool. If institutions were targeting the highest yield stuff, and left the lower yield stuff to hit the fractional market, what you're seeing makes some sense. In any case tomorrow's article goes through a slew of borrower attributes and compares them across initial list status.
Bryce I look forward to reviewing your work. I guess I am focusing more on this idea that within equal credit grades, retail investors are being offered notes with riskier traits. There's no way I wouldn't disclose that in an S1 if I were LC. I am sure you will run a more rigorous statistical analysis.
My analysis was extremely simple (for the mass audience on Peter's blog), but it did look at a number of borrower traits. If there are other traits you think are key, I can add them in. Given your work above, I may also play with the defaults a bit. But, I think from a disclosure standpoint, all that we need worry about is whether the characteristics that are known at the time of loan listing are balanced across whole vs. fractional.
That's right, Rawraw. We know they keep some facets private. However, I think it would be exceedingly hard to have so many factors apparently equal, and then partition along the remainder and achieve a big default shift. It's worth a critical look, but we're only a year into the default curve.
I don't think I agree. As a securities matter, the only thing LC has told us about the risk of a note is their assigned letter grade. If it is true that, within notes that LC has told us should have equal risk characteristics, the notes offered only to large investors are less risky, I have to think that's a disclosure item. I agree that it may be too early to make any broad conclusions, though.
With the understanding that these loans are still quite early in repayment, my own table construction from the same data extract that I used for the article yields the following. I do not see any cause for concern here, so I guess I disagree with however the data to which you refer was prepared. I aggregated the codes some for simplicity. It's just a loan count, so not weighted by loan amount or amount in the various categories, but I just don't see it mattering.
. tab status whole if policy_code==1, col
+-------------------+
| Key |
|-------------------|
| frequency |
| column percentage |
+-------------------+
| whole
status | 0 1 | Total
------------+----------------------+----------
Charged Off | 153 52 | 205
| 0.24 0.22 | 0.23
------------+----------------------+----------
Current | 62,359 22,323 | 84,682
| 95.88 96.13 | 95.95
------------+----------------------+----------
Impaired | 732 199 | 931
| 1.13 0.86 | 1.05
------------+----------------------+----------
Paid | 1,793 647 | 2,440
| 2.76 2.79 | 2.76
------------+----------------------+----------
Total | 65,037 23,221 | 88,258
| 100.00 100.00 | 100.00
Bryce - what happens to your analysis when we look at lower grade loans issued b/t October 2012 and, say, May 2013? I'm wondering if that might ferret out any significant gap in the default rates...
I doubt the time restriction will matter, because the entire whole loan program is basically October 12 to July 13 (in that data), but for the hell of it, here it is. D-G. Still no discrepancy on the surface. At this point, it might be easier to provide the code on which the other analysis is based and I'll try to find the error. The assignment is random; there aren't going to be any differences with 90,000 loans.
. tab status whole if policy_code==1 & inrange(list_month,10,17) & inlist(grade,"D","E","F","G"), col
+-------------------+
| Key |
|-------------------|
| frequency |
| column percentage |
+-------------------+
| whole
status | 0 1 | Total
------------+----------------------+----------
Charged Off | 61 17 | 78
| 0.53 0.43 | 0.50
------------+----------------------+----------
Current | 10,790 3,708 | 14,498
| 93.15 93.26 | 93.18
------------+----------------------+----------
Impaired | 289 91 | 380
| 2.50 2.29 | 2.44
------------+----------------------+----------
Paid | 443 160 | 603
| 3.82 4.02 | 3.88
------------+----------------------+----------
Total | 11,583 3,976 | 15,559
| 100.00 100.00 | 100.00