Auto Loan Securitizations – Visualization & Analysis
Auto lending is one of the largest consumer credit sectors in the United States, with over $1.1 trillion in outstanding receivables.
While the headline numbers on this asset class are well-known, detailed asset-level data have traditionally been difficult to obtain for those not in a privileged position (e.g. analysts on a wall street ABS desk). Fortunately for us, the SEC passed a rule in 2014 specifying, “offerings of asset-backed securities backed by residential mortgages, commercial mortgages, auto loans, auto leases, and debt securities (including resecuritizations) must comply with asset-level disclosure requirements no later than November 23, 2016.” These asset-level disclosures are made using a form known as ABS-EE and conform to a standardized XML format. Our friends at Finsight, who also provide securitization issuance data for Orchard’s Weekly Online Lending Snapshot, have conveniently listed and categorized many of these ABS-EE data tapes on their website.
Today, Orchard will analyze the Feb 2017 data tape submissions of several of the largest auto loan securitization trusts, specifically:
- Ally Financial Auto Receivables Trust 2017-1
- Santander Drive Auto Receivables Trust 2017-1
- Carmax Auto Owner Trust 2017-1
- California Republic Auto Receivables Trust 2017-1
- Americredit Auto Receivables Trust 2017-1
- Ford Credit Auto Owner Trust 2017-1
We can use these datasets to learn about the general nature of these auto loans, their borrowers, and the assets against which they are secured.
Volumes & Population
As we can see from the above graph, we are analyzing a population of $8 billion in original loan principal and $6.55 billion in outstanding receivables. The largest trust in the population belongs to Ford Credit, while the smallest is that of the California Republic.
The majority of the loans we will analyze were originated in the last few quarters, though some were booked as long ago as 2010. Below, we show the breakdown of both original principal and remaining balance by origination date.
The Cars Themselves…
An auto loan is effectively just a consumer term loan, with an interest rate, a principal, and an amortization schedule. What makes it more interesting, of course, is the underlying collateral, the car or truck. Below, we examine the various types of automobiles in our dataset.
Unsurprisingly given the existence of Ford Motor Credit as an issuer in the dataset, Ford vehicles predominate. Plymouth, a brand no longer in existence, is the least prevalent make. The specific model names are so numerous that the best way to visualize them is perhaps as a word cloud, with word size proportional to frequency in the dataset.
Interest Rates & Credit Quality
In the below graph, we see the distribution of interest rates by issuer, a colorful picture that illustrates the diversity of pricing both among and within auto lenders. While the Ford Credit trust in our dataset maintains an average borrower interest rate of 2.74%, Santander Drive averages 16.5% annual interest, and the others fall in the middle.
Given that a loan’s interest rate is typically a function of borrower credit profile, it makes sense to also look at the FICO distribution by issuer to see if we observe a predictable pattern. Indeed, Ford Credit’s borrowers are distributed among far higher credit scores than their counterparts, and the loans in the Santander and AmeriCredit trusts belong to less prime borrowers.
When viewed as a violin/jitter plot, it becomes clear that higher credit scores are correlated with lower interest rates.
By examining several of the variables in the dataset together, we can uncover more interesting information on the relationship between borrowers, their vehicles, their credit characteristics, and the parameters of their auto loans.
In the graph below, we can see the average borrower credit score by vehicle make. Unsurprisingly, Lincoln and Ford come out on top, likely due to the large cohort of prime Ford Motor Credit loans in the dataset. Interestingly, the next highest make is Subaru, which lines up with a 2014 Orchard study in which we built a Bayesian classifier to predict default rates given a borrower’s written description of the reason for applying for a LendingClub loan. We found that the word “subaru” was an indicator of low likelihood of default!
The presence of a co-signer on an auto loan is another interesting indicator. In our dataset, just over a third of loans have been co-signed. The graph below shows a wide variance in co-signer use by brand, with Saturn, Subaru, and Kia buyers exhibiting a much higher rate of co-signer use than that of Tesla or Maserati buyers.
The dataset also contains information on whether a car is new or used. From the two graphs below, we can see that new car borrowers tend to have higher credit scores and lower interest rate loans.
In summary, the ABS-EE loan-level disclosure datasets provide a compelling glimpse into the underlying collateral of automotive asset-backed bonds. While we have focused today’s post primarily on loan characteristics and borrower demographics, we look forward to future analysis of performance, deal structure, and bond pricing.