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A Dive Into The Lending Club Data

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Re: A Dive Into The Lending Club Data

#21

Post by hueyp »

Amorymeltzer wrote: post #7

The employment length is really bugging me. I've always selected people with a few years at their current job, leaning towards higher, because it feels safe, but this says that My other big hit is 3 versus 5-year terms. Anyone here care to comment? I like the 36 months because it feels more liquid and when I started I wasn't sure LendingClub was going to be around for a decade or more. Beginning to think I should rec…

> if the rates are much higher compared to a marginal increase in risk

Exactly. Same thing with public records -- having a public record could very well mean you have a higher default rate but what is important is LC punishes it more than they should so its a value investment.

We invest via a model (not filters) and the whole idea behind the model isn't to find what criteria makes someone less likely to default in absolute terms, but what makes one D2 loan less likely to default than another D2 loan.

Re: A Dive Into The Lending Club Data

#22

Post by radmuzom »

I build statistical models for banks which help assess the risk of a loan. Effectively, my models will get converted into the grades (A, B, C, D, etc.) mentioned in the article. The strategies (second chance, family guy, safe haven) are generally consistent with experiences from the portfolios of most financial institutions.

However, I am skeptical (prove me wrong) of the statement in the article - "Lenders get a return on their investment that is typically much better than traditional Certificate of Deposit or Saving Accounts". In finance terms, I will be surprised if they have a higher RAROC [1] as compared to large banks. If they really do, then congratulations (you will put banks out of business in a few years)??

[1] https://en.wikipedia.org/wiki/Risk-adjusted_return_on_capita...

Re: A Dive Into The Lending Club Data

#23

Post by ClementM »

radmuzom wrote: post #22

I build statistical models for banks which help assess the risk of a loan. Effectively, my models will get converted into the grades (A, B, C, D, etc.) mentioned in the article. The strategies (second chance, family guy, safe haven) are generally consistent with experiences from the portfolios of most financial institutions. However, I am skeptical (prove me wrong) of the statement in the article - "Lenders get a ret…

Glad that my findings match yours !

I think it does beat a C.D. from a risk/return perspective. It's probably higher risk than a C.D. but returns largely compensate for it I believe.

To me this is possible because the Lending Club is desintermediating a business that was traditionnally 'high margin'.

Re: A Dive Into The Lending Club Data

#24

Post by radmuzom »

Amorymeltzer wrote: post #7

The employment length is really bugging me. I've always selected people with a few years at their current job, leaning towards higher, because it feels safe, but this says that My other big hit is 3 versus 5-year terms. Anyone here care to comment? I like the 36 months because it feels more liquid and when I started I wasn't sure LendingClub was going to be around for a decade or more. Beginning to think I should rec…

> but this says that When you say better, do you mean risk or return? First of all, you are looking at the variable in a "univariate" sense,i.e, the relationship of the default rate or return by the categories of this variable. But their internal model is multivariate - there may be other factors influencing risk or return which is not obvious in the univariate dimension. It also depends on the power of this variable in predicting risk. And finally, lower risk may mean lower return - you just need to find the efficient frontier :) - http://www.investopedia.com/terms/e/efficientfrontier.asp.

Re: A Dive Into The Lending Club Data

#25

Post by dragonwriter »

radmuzom wrote: post #22

I build statistical models for banks which help assess the risk of a loan. Effectively, my models will get converted into the grades (A, B, C, D, etc.) mentioned in the article. The strategies (second chance, family guy, safe haven) are generally consistent with experiences from the portfolios of most financial institutions. However, I am skeptical (prove me wrong) of the statement in the article - "Lenders get a ret…

> In finance terms, I will be surprised if they have a higher RAROC [1] as compared to large banks. If they really do, then congratulations (you will put banks out of business in a few years)??

Or, more likely, just drive down bank profit margins.

Re: A Dive Into The Lending Club Data

#26

Post by ThrustVectoring »

Amorymeltzer wrote: post #7

The employment length is really bugging me. I've always selected people with a few years at their current job, leaning towards higher, because it feels safe, but this says that My other big hit is 3 versus 5-year terms. Anyone here care to comment? I like the 36 months because it feels more liquid and when I started I wasn't sure LendingClub was going to be around for a decade or more. Beginning to think I should rec…

For students going to a particular university, math SAT scores are inversely correlated with verbal. If students had a higher math SAT and a higher verbal SAT, they'd be at a better school (and worse math + worse verbal = worse school).

For debtors inside a certain grade, it looks like employment history and other creditworthiness metrics are inversely correlated. So I suspect that it's less employment length being an anti-signal, but rather within the grade people with short employment length have compensatory advantages to stay in that grade.

Re: A Dive Into The Lending Club Data

#27

Post by guelo »

radmuzom wrote: post #22

I build statistical models for banks which help assess the risk of a loan. Effectively, my models will get converted into the grades (A, B, C, D, etc.) mentioned in the article. The strategies (second chance, family guy, safe haven) are generally consistent with experiences from the portfolios of most financial institutions. However, I am skeptical (prove me wrong) of the statement in the article - "Lenders get a ret…

I don't know much about the banking industry but savings accounts and CDs have always felt scammy to me. They're marketed to the rubes that have no idea what they're doing so they can get away with not being competitive with other financial instruments.

Re: A Dive Into The Lending Club Data

#28

Post by jklein11 »

guelo wrote: post #27
radmuzom wrote: post #22

I build statistical models for banks which help assess the risk of a loan. Effectively, my models will get converted into the grades (A, B, C, D, etc.) mentioned in the article. The strategies (second chance, family guy, safe haven) are generally consistent with experiences from the portfolios of most financial institutions. However, I am skeptical (prove me wrong) of the statement in the article - "Lenders get a ret…

I don't know much about the banking industry but savings accounts and CDs have always felt scammy to me. They're marketed to the rubes that have no idea what they're doing so they can get away with not being competitive with other financial instruments.

The reason why savings accounts and CDs have such a low interest rate is because they are far less risky than other financial instruments.

If you compare them to other assets with a similar risk profile and payment structure, such as short dated treasury notes and annuities, you will find that the rates are at least competitive.

Disclaimer: My response has a US bias.

Re: A Dive Into The Lending Club Data

#29

Post by jlittel »

ClementM wrote: post #14
Amorymeltzer wrote: post #7

The employment length is really bugging me. I've always selected people with a few years at their current job, leaning towards higher, because it feels safe, but this says that My other big hit is 3 versus 5-year terms. Anyone here care to comment? I like the 36 months because it feels more liquid and when I started I wasn't sure LendingClub was going to be around for a decade or more. Beginning to think I should rec…

Also, it's pretty instructive to look at the Lending Club grading algorithm in details. They made it public at some point. Now they are a little less transparent about it. But some details can be found in their SEC prospectus. I can link that up as well if you guys want.

I'd love to see any info.

Their current offering document is here[1], but I don't see much mention of specifics. There's some detail on mapping to grades on p42 of the Aug 22 doc, as well as interest rates charged for each risk category.

[1]https://www.lendingclub.com/info/prospectus.action

Re: A Dive Into The Lending Club Data

#30

Post by techcreditcard »

radmuzom wrote: post #22

I build statistical models for banks which help assess the risk of a loan. Effectively, my models will get converted into the grades (A, B, C, D, etc.) mentioned in the article. The strategies (second chance, family guy, safe haven) are generally consistent with experiences from the portfolios of most financial institutions. However, I am skeptical (prove me wrong) of the statement in the article - "Lenders get a ret…

Your background sounds interesting! I'm working on bringing a credit card to the subprime market. Would be great to connect with you.
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