Lending Club raises guidance

Hi all,

Quick interesting note: Lending Club, a “potential” competitor to UPST (yes, I am aware, they are not as good!) just raised their 2021 target to 750-780M from 530M. That is expected growth in the ~135% if I am not mistaken.

Bodes well for UPST - we should hope it is even more than that!



Thanks for the info!

It’s up 43% after hours on the news. Hopefully, this is a good omen for Upstart.


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As XMFSandman also pointed out yesterday, LendingClub is still projecting loan originations for 2021 at below that of 2019 or even 2018. They are still trying to return to previous precovid numbers.

In 2019 they originated $12.29B, net revenue 758.6M (+9% YoY)
In 2020 they originated $4.343B, net revenue 314.7M (-58.5% YoY)
They today are guiding 2021 at 10.2B originations and 750 to 780M net revenue. This is ~0% growth from 2019.

I suspect if they had better AI underwriting capabilities, they could have grown net revenues and loan originations from 2020 onward to 2021 in spite of COVID.

Which is what Upstart accomplished, high growth through COVID:

2019 total revenue 164M (+65% YoY)
2020 total revenue 233.4M (+42% YoY)
2021 total revenue guidance 600M (+157% YoY). This is 265% growth from 2019.


The difference is indeed striking.

Regarding Upstart, I still don’t really understand what caused the sudden acceleration in revenue (without significant impact of the car loans)and guidance last quarter. Is it just the models and marketing that are getting better?

From the Q1 transcript:
“But the big win we saw in the first quarter included an upgrade to the algorithm that governs how these models are blended together. This upgrade led to higher approval rates and lower interest rates, which, of course, translates into more loans.”


Conversion rates can have a big effect on revenue. Upstart increased their conversion rate QoQ from 17.4% in Q4 2020 to 22% in Q1 2021. Even if the amount of customers remained the same, revenue would be greatly impacted. Now include higher conversion rates with a massive increase in customers (due to new partnerships with banks, better marketing), and you end up with the quarters Upstart is putting out.


It seems that LendingClub is a worthy competitor to Upstart in terms of automated approvals. From the call:

“These models are built on more than 150 billion cells of data and more than a decade of experience across over $65 billion in loans.”

We also optimized our application funnel and drove automated decision rates back to north of 70%."

Notably, LendingClub now has a banking license, so it can keep the entirety of its origination fee. (Upstart charges 8%, keeps 6% net - rest is passed on to the bank partner.)

So, here’s my question…we know unsecured loans are big business, and approvals based on criteria other than FICO scores are undeniably a trend (one with governmental encouragement, if handled correctly - see last week’s WSJ article).

Does Upstart have a moat? And if it doesn’t, does it matter, if the winds are blowing in its favor?

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I suspect if they had better AI underwriting capabilities, they could have grown net revenues and loan originations from 2020 onward to 2021 in spite of COVID.

Which is what Upstart accomplished, high growth through COVID:

The automated approval process is where better AI underwriting capabilities comes in. And this is where traditional banks have become complacent, or lazy, in their approach. They don’t want to sit down and talk loan terms with you. And they don’t have an automated approval process as good for actual loans. They’ll set you up with a HELOC, or a credit card, and you can borrow what you want, up to the credit limit. And for that they do have reasonably good algorithms.

For now that’s an advantage to Lending Club or Upstart. But that may well be temporary. Someone else wondered how big their moat is? How “big” a moat is really means how long it will last. And the banking sector has enough resources that they’ll eventually have technology as good as their competitors.

The only concern is that Lending Club and Upstart may be seeing their best days right now. OR maybe last quarter.



"These models are built on more than 150 billion cells of data and more than a decade of experience across over $65 billion in loans.

If LendingClub’s models are so great, why did their revenues plummet 58.5% from 2019 to 2020? With such vast, large datasets why could they not continue to properly underwrite loans? How come Upstart, with smaller available datasets, was able to grow revenues by over 40% instead?

We also optimized our application funnel and drove automated decision rates back to north of 70%."
From their earnings call yesterday:
“we continue to focus on serving our large and loyal days of over 3.5 million members…a large portion of our loan volume continues to go to our existing customers.”
It’s incredibly easy to underwrite your existing customers, and thus automate decisioning for them. They don’t break out their actual numbers on new vs existing borrower loan origination. What’s their true automated decision rate for a new borrower?

From their earnings call yesterday: “We resumed marketing and return to a more normalized credit posture, with a continued focus on higher quality issuance.” They are stuck on “higher quality issuance” equals “higher FICO scores”. We already know FICO scores are not predictive enough by itself, but it’s what they’re stuck on.

I mean, if their underwriting technology is so good, why has their average weighted FICO scores trended upward over the years? Shouldn’t they be able to pick out the subprime borrowers with better accuracy?
From KBRA data: As of September 25, 2017, the weighted average FICO score is 692. But, by 2020 it had trended up to 713.
To hammer this point home: https://i.imgur.com/4sIm1Lb.png
Why did KBRA have to raise their loss projections for every single LendingClub trust from 2017P1 to 2019P1?
But Upstart’s loss rates for 2017 to 2019 were lowered across the board in comparison?

Also, why don’t they release conversion rate numbers publicly? Shouldn’t they have high conversion rates if they had better technology? Are their conversion rates any better than traditional lending peers?
Remember, from information made available by the FTC case against LendingClub, all we know is their application-to-loan conversion rate decreased from an average of 6.2% in June 2017 to April 2018 to an average of 5.6% in June and July 2018. A stark contrast to Upstart’s 22% last quarter.

And, if they truly had superior technology and predictive models, why did they shut down peer-peer lending in December 2020? Why did they have to pivot their entire business into actually becoming a bank?

The answer to the above is simple. LendingClub lacks the ability to pick out who of the below-prime borrowers will actually pay you back. They can’t do it any better than other traditional lenders/underwriters. There’s just no competitive advantage in their underwriting.
For Upstart, based upon their past earnings reports and securitized loss rate data, we can see they have an underwriting technological superiority.


The lending decisions at Lending Club (LC) have been only partially made by LC. I was an individual LC lender up until LC severed their ties with individual lenders at the end of 2020. It’s possible that with only banks as lenders now that LC has changed their practices but here is how it worked at LC until the end of 2020:

  1. LC collects a loan application.
  2. LC provides anonymous summary data and an initial grade from E1 to A5 based on their models for investor members. Interest rates offered are based on loan grades and duration.
  3. Investor members choose Lloyd’s style which loans to underwrite. Some investors are looking at loans one by one like I did and others use some form of automation to invest in everything that meets their criteria.
  4. If a loan draws enough investment the borrower will be offered the loan.
  5. If the borrower accepts the loan then the loan contract is finalized and the loan issues.

My point is that with LC process the volume of issuance has depended not only on the LC risk model but also investor and consumer demand for LC notes.

Here is an excerpt from the Q2 LC call that strongly indicates that LC is changing their process:

Scott Sanborn

I’ll maybe start on the, the investor side, Tom and you can talk a little bit about the liability. So there we’ve seen strong investor demand of kind of across the spectrum of investor types. As we mentioned, we’ve added year-to-date, both quarters, several new multiple asset managers and multiple banks. And if you call the last quarter, we talked about how, as a whole, the asset class held up really well last year, and LendingClub specifically held up better than the competitive set, I think one of the things we perhaps didn’t anticipate was that our status as a bank does do something for us in multiple ways, one for banks evaluating the asset, they know we’re held to the same standard as they are from a regulatory perspective.

And the second is, we’re eating our own cooking right. So that gives people a lot of confidence and how we view the importance of credit quality. So say those things, make rational sense but he until you see him in action, which we really saw this quarter. There were some benefits that we perhaps underappreciated coming into the combination. Tom, do you want to talk about?


So with LC I think we need to view the beginning of 2021 as a potential inflection point and we really can’t use their pre-2021 results to gauge their competitiveness. It seems to me that LC is still relying on external partners to underwrite loans but there may be some shift towards sources of financing where LC has more control.