LendingClub And OnDeck Will Die In The Next Recession

| About: LendingClub Corporation (LC)

Summary

LendingClub’s (and that of other p2p lenders) business model is a race against time, but without a finish line.

Already, LendingClub’s algorithm is underperforming.

Moreover, because a recession is eventually inevitable, LendingClub will eventually go under.

I am an advocate for using insider activity as a leading indicator for predicting stock price movement. Being so, I pointed out in a previous article on LendingClub (NYSE:LC) that despite the company's hardships, management is being rewarded to a great degree. My article was not exactly well received for two reasons:

  1. The management compensation increases can be explained as an attempt to keep talent from leaving the company during hard times.
  2. Readers assumed that I was making a causal prediction: Management comps foretell the bankruptcy of LC.

While the first point is justifiable, I still disagree, and I implore you to read my previous article as to see my viewpoint. As I mentioned previously, I attempted to reach out to LC for clarification but received no response. As insiders know more about a company than we investors do, they likely know quite well that they are in dire straits, which brings me to my next point.

The second point was a misunderstanding. I am already assuming that LendingClub will eventually perish. I did not make this thesis clear in my last article, but I plan to do so today.

Why LendingClub Must Go Bankrupt

LendingClub's business model is a race against time, but without a finish line. Everything I'm about to say also applies to OnDeck Capital (NYSE:ONDK) and all other p2p lending businesses. LendingTree (NASDAQ:TREE) is an exception, as this company uses a different business model and should be dissected as a lead-generation company.

LendingClub's business model relies on probability theory. Specifically, the company uses an algorithm to quickly determine the probability of a loan applicant defaulting. The algorithm uses this probability along with an expected ROI to arrive at a decision on the loan and has been increasingly relaxed, allowing for higher default rates.

Finding a Benchmark

This business model has a number of problems. First, it is relatively new. The p2p lending industry does not yet have benchmark default rates.

Without a benchmark, LendingClub is grasping in the dark, somewhat arbitrarily determining an acceptable write-off rate. Of course, over time, the p2p lending industry will find its benchmark and can more effectively choose its applicants. But until that point, a huge set of problems plagues the company as it lowers interest rates and increases the default rates arbitrarily.

A Broken Algorithm

Already, LendingClub's algorithm is underperforming. The actual write-off rate is roughly double that of the company's internal estimates. This alone should be a red flag: The algorithm is not working, as a simple look at the actual versus expected write-off rates reveals:

Click to enlarge

Of course, with plenty of cash on hand, LendingClub has time to iron out the kinks. But while it does so, it exposes itself to what is possibly an insurmountable amount of risk. Much of this risk is passed onto investors, who are forced to trust the grades LendingClub gives to loan applicants.

Exploitation of the Loan Time frame

Investors burned by this system will be the nodes in a system that dismantles LendingClub's reputation. But that's only one side of the story. The other side lies in the debtors exploiting LendingClub's algorithm.

The algorithm is only a soft check and is restricted by time. An applicant can stack loans from one or more p2p business in a manner undetectable to these algorithms. For example, an applicant can apply for and receive a loan from OnDeck and then immediately turn to LendingClub for another loan.

The second loan is given without regard to the first loan. In other words, while the algorithm should recognize an increased risk of default because of a new, outstanding loan, the increased risk simply does not register. With p2p lending companies reporting loans monthly, applicants can stack multiple loans within a 30-day period without experiencing a change in their risk profiles.

Clearly, more time is needed for LendingClub to fix both the algorithm's accuracy and the ability to exploit the algorithm. To run on algorithms and not human credit checks is possible but not currently working. Essentially, LendingClub is running a trading algorithm that looked good in the backtest but fails on the live market.

A Recession will Kill LendingClub

But a much larger problem is that LendingClub's only solution to this problem is time, and time is also LendingClub's guaranteed executioner. Eventually, the market will see a recession. I explain the two types of recessions in this article, but for LendingClub, either recession will cause the company to fail.

In a Type I recession, which is a natural phase of a business cycle, default rates increase. LendingClub might have internal models that predict the company can withstand a significant default rate increase. However, as we've seen, LendingClub's models are unreliable.

In addition, companies typically use the most recent recession data to predict the next recession. Companies take the most recent data to construct a distribution of all possible outcomes, ignoring the data that we have not yet witnessed in the past. The result is a Guassian distribution that neglects both kurtosis risk and skew risk, giving companies an overly optimistic representation of the probability set of outcomes when in fact the true distribution is a Taleb distribution, not a Guassian distribution:

LendingClub and other companies have fallen into such a trap, as evidenced by the insignificant amount of cash held to cover for losses. LendingClub's cash, for instance, cannot cover one year's worth of loans. The company's statement that it can cover for a recession should not be taken as fact as it is built on a faulty assumption of the magnitude of the average recession.

While single-digit yields might attract applicants, at the end of the day, the loans are unsecured loans. The rate of income cannot keep pace with the rate of losses via defaults during a Type I recession. LendingClub is exposed to significant downside without the tools that other financial institutions (e.g., banks and credit card companies) use to weather a Type I recession.

The much more rare Type II recession is equally deadly for a company such as LendingClub and is part of the "fat tail" in the Taleb distribution that is not the basis for the Moody's recession simulations on which LendingClub built its recession scenario. In this environment, businesses and households shift their focus to paying down debt and therefore have no need for loans. Without loan applicants, LendingClub has no business. As Japan has shown, changing interest rates has no effect during a Type II recession, and LendingClub will therefore have no tools to attract borrowers.

Because one of these recessions is inevitable, LendingClub will eventually go under. Right now, it struggles to evolve its algorithm in ignorance of the endgame. The company could very well improve in the short term, but any money you put down on this stock will eventually be gone with the wind.

A note for TREE investors: Despite having a different business model, TREE is unfairly punished whenever LC or ONDK suffers bad news. TREE will hurt, too, during a recession, especially during a Type II recession, in which borrowers disappear. But as long as the market conditions are still good, as they are now, TREE investors should look to buy on the dips brought about by negative news from LC and ONDK.

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