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The Taxi License: A Crumbling Medallion

|Includes: Medallion Financial (MFIN)

Summary

A case study of Medallion Financial Corporation using KRIS default probabilities.

This analysis by Kamakura's Suresh Sankaran shows how modern default probabilities provide clear signals for timely entrance to and exit from corporate credit exposure.

While the analysis is focused on a single corporate credit, the principles apply to all corporate exposures.

This note was guest authored by Suresh Sankaran of Kamakura Corporation.

This article explores the demise of the medallion (an exclusive licence to drive a taxi), consequent to the UBER phenomenon. It analyses the performance of Medallion Financial Corp. (NASDAQ: MFIN) {"the company", "Medallion"}, which, through with its subsidiaries, operates as a specialty finance company in the United States. It originates, acquires, and services loans that finance taxicab medallions and various types of commercial businesses.

The objective of this write-up is to showcase how the Kamakura Risk Information Services ("KRIS") default probabilities subscription service assists users to manage exposure entry and exit based on Kamakura Default Probability ("KDP") movements.

This write up could be a harbinger not just for the United States but also for countries around the world that operate a similar taxi model.

MFIN's last 10-Q filing has suggested that as of September 30, 2016, 15.9% of its managed medallion loan portfolio and 19.4% of its on-balance sheet loan portfolios were 90 days or more past due, compared to 4.1% and 3.8% at December 31, 2015. Furthermore, of the $300 million in total taxi loans on the Company's books, $86 million are not current on their obligations. That's twice the level of a year ago. The over 90 days past due loans have quintupled… The less obvious but more worrying development is that the net worth of Medallion Bank,- the key subsidiary of the Company, may be in danger. If net worth drops too low from write-downs and write-offs, MFIN will have a problem with the bank regulators. These problems are reflected in the stock price which has shown a steady decline.

It is evident that with the rise of organizations like UBER, the taxi industry is in freefall, and there is seemingly no way out for all players including MFIN. This document highlights how KRIS default probabilities and related risk measures would have allowed investors to exit from a position in MFIN well before the conditions leading to its decline in 2016.

The default probabilities produced by the KRIS service include both the best practice reduced form default probabilities and the older and less accurate Merton model default probabilities. In this note, we use the KRIS version 6.0 reduced form default probabilities, the newest and most accurate model in the KRIS default models framework.


The Kamakura riskiest companies' list as on 27 February 2017, lists MFIN at the 95th percentile of all listed companies in the United States, as seen below. It is also instructive to see the evolution of riskiness over the past eighteen months.

It can be clearly seen that the taxi industry crisis has impacted the entire term-structure of KDPs with the values moving from a very respectable cumulative 10% on December 30, 2015 to close to 40% on February 24, 2017. The riskiness percentile rank has moved from a low of 52% to a staggering 95%, which makes MFIN one of the riskiest companies in the USA. This increase in riskiness percentile rank is also reflected in the stock prices, as noted earlier, which has been in steady decline.

Now, let us turn our attention to the details of the probabilities of default, the key creditworthiness assessment metric. The figure below shows the history of the 1-month (in red), 1-year (in blue), 5-year (in orange), and 10-year (in green) default probabilities for MFIN on 24 February 2017:

In Kamakura Corporation's popular troubled company index, a firm is considered "troubled" if its default probability exceeds one percent. The graph above shows that the entire term structure of default probabilities of MFIN gradually increased, and the one-year KDP exceeded 5.00% in February 2017, consistent with the industry problems. However, it is illuminating to note that a full 9 months before this, the company was showing a deterioration in its creditworthiness, starting in July 2016, where all four term structure points on the default curve moved up over 1%. For a fixed income investor, this is tremendous early warning, and highlights exit options well before downturn in fortunes. This makes for particularly interesting reading in conjunction with the market issues identified, as it is evident that even before the troubling news on the taxi industry became public knowledge and discussed in the public domain in 2016/17, the company was in troubled waters. While the taxi industry crisis outlined a specific short-term problem with the company, the Kamakura Default Probabilities showcased the increasing risk both on account of the changing market landscape and of deteriorating fundamentals. It can be argued compellingly that the KDPs provided a portent of the writing on the wall, where the 1-year KDP tracked the industry crisis whilst the 5-year and 10-year KDPs identified a more structural problem.

Another indicator that is very valuable as an early warning signal is a comparison to the industry peer group, which in the case of MFIN is the Diversified Financials peer group. It can be seen clearly in the graph below that the company's one-year default probability moved to well above the 90th percentile, and indeed much higher than 2 standard deviations above the median, in mid-2016. This is another warning, more than a year ago, to exit from any holdings of MFIN. Through late 2016, this trend was maintained, and it was clear to any observer that the company was gradually moving from its already risky position close to the sector's 75th percentile of riskiness to well over the 90th percentile.

A critical output from KRIS is the implied ratings framework, where a comparison is made of KDPs to their perceived implied ratings. A glance at this ratings table as of February 24, 2017, outlined in the graphic below, clearly indicates a forecast of deteriorating creditworthiness, and a 99% cumulative probability of the ratings careening to default.

Medallion has an outstanding bond issue, and its details are as follows:

It is interesting to observe the credit spreads on this outstanding bond. Since the last trade was observed on April 20, 2016, we look at the spreads over U.S. Treasuries on that date: the spread is an astronomical 52.36%. The lack of trades in the market and the burgeoning spreads are also indicators of troubles ahead for MFIN.

KRIS also provides models to evaluate the banking subsidiaries of holding companies. It is also instructive to observe Medallion Bank's KDPs from 2015.

As quarterly filings indicate increased write-downs, KDPs show an uptick, and this is reflected in the performance of the holding company as well.

A final thought is that the investor should not assume that just because Medallion is in the financial services sector, it is correlated to the factors that drive the riskiness of that of other banks. Here is a comparison of the default correlation between MFIN and a selection of banks in the United States.

It can be easily seen that while the banks are very highly and positively correlated, these correlations become weak, and negative when compared to MFIN. A common mistake would have been to evaluate MFIN in the context of the performance of other banks, but it should not be forgotten that MFIN is specialized, and riding on a toxic underlying premise, which has become obsolete.

As early warning indicators go, it does not get any clearer than this, where a full 6 months before this predicament came to pass, information in KRIS clearly outlined an exit strategy.

The KRIS default probability models are benchmarked on more than two million observations of firms of all types. The total number of defaults used in the current version 6.0 models is more than 2,600. The unparalleled volume of data and the research insights of Kamakura's Managing Director Professor Robert Jarrow make the KRIS default probability service the most accurate early warning credit risk assessment indicator framework available. That is one of the reasons why Credit Magazine named both KRIS and the Kamakura Risk Manager Software package "Innovations of the Year". For more information about KRIS default probabilities, please contact your Kamakura representative or e-mail Kamakura's credit experts at info@KamakuraCo.com.

Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.