Contributed by Adam Strochak
Our note last month about the Mace decision from the bankruptcy court in Tennessee, promised a follow-up post on cramdown interest rates, so here goes. As noted in our Throwback Thursday post, the lead case on cramdown interest rates – the Supreme Court’s decision in Till v. SCS Credit Corp., 541 U.S. 465 (2004) – left us with less than crystal clear guidance on cramdown in chapter 11 cases. In fact, as one financial advisor asked rhetorically at a recent conference on restructuring commercial real estate loans, “Do you mean to tell me that I should look to a chapter 13 case that set the cramdown interest rate on a used pickup truck for guidance on the correct rate under a chapter 11 plan for a multi-billion-dollar commercial mortgage portfolio?” Well, um, yes.
In Till, the Supreme Court determined that the rate of interest on a cramdown note in chapter 13 should be determined by the “formula approach,” which starts with the prime rate – the interest rate a commercial bank would charge a creditworthy commercial borrower – and then adjusts that rate upward to account for the additional risk of non-payment posed by lending to a bankrupt debtor. Applying this method to a chapter 11 case should be simple enough because the provision of chapter 13 permitting cramdown on a secured creditor (11 U.S.C. § 1325(a)(5)(B)) is substantially the same as the one in chapter 11 (11 U.S.C. § 1129(b)(2)(A)(i)). Not so fast. In rejecting other approaches based on market measures of interest rates, the Court noted in a footnote that in chapter 11 there is a “free market of willing cram down lenders” and pointed to the availability of debtor in possession financing as evidence of this. Justice Stevens, writing for a plurality of the Court, then went on to suggest that, “in a Chapter 11 case, it might make sense to ask what rate an efficient market would produce.” 541 U.S. at 477, n.14.
The Till decision leaves us with three questions to ask in each chapter 11 cramdown situation. First, is there an “efficient market” for comparable secured credits such that a market rate can be determined for the cramdown loan? Second, if there is no efficient market and a formula approach is required, is the prime rate the correct base rate from which to start? Finally, once an appropriate base rate is selected, how much of a risk premium should be added to account for the risk of non-payment?
Equating the availability of DIP financing with the existence of an “efficient market” for secured exit financing seems quite a stretch. The “market” for DIP loans is not like regular credit markets and not like the markets for exit financing. DIP lending is highly specialized and DIP lenders often have other positions in the capital structure of the debtor. A DIP credit is a loan to a highly distressed borrower – one that is, by definition, either in or on the brink of chapter 11. DIP borrowers are forced by circumstances to obtain credit in order to save themselves from liquidation and often have little negotiating leverage. While DIP loans may in fact be very low risk credits, the reality is that they are priced as very high risk credits. The efficient market inquiry should be focused not on the availability of DIP credits, but on the availability and pricing of loans comparable to the cramdown loan in the general credit markets. During the financial crisis in 2008-09, for example, there simply was no money available for lending on commercial real estate; not only was there no efficient market, there was no market at all. Under those circumstances, the formula approach makes sense.
The Supreme Court in Till presumed that the starting point for the formula approach was the prime rate, but it’s not set in stone that the prime rate is the right starting point for a commercial mortgage loan or other commercial secured credits. The prime rate is typically used for short term loans, and; in some cases, a secured credit might be available below the prime rate. A better approach, and one used in many of the cramdown cases, is to start with a true risk-free rate that can be matched to the term of the cramdown loan – rates on US Treasury debt. Although the persistent US budget deficit and recent political obstacles to raising the US debt ceiling have focused the attention of ratings agencies and investors on the credit-worthiness of US obligations, the rate on a US Treasury bill remains the closest thing we have to a risk-free interest rate.
The existence of an efficient market and the choice between prime or treasury rates are more or less binary choices. Selecting a risk premium, however, involves evaluating multiple factors to match the ultimate rate selected to the risk of default posed by the particular debtor in question. The risk premium, as the Supreme Court’s reasoning in Till shows, is not intended to compensate the lender for the opportunity cost of making a forced loan or to fold in a profit margin; it is intended only to account for the risk that the lender might not get paid. Although the Supreme Court punted on the appropriate range for risk premiums, it noted that other courts had found 1% to 3% to be the goalposts and most lower-court decisions have been in this range.
Part of the Supreme Court’s rationale for selecting the formula approach over other methodologies was the belief that it would “minimize the need for expensive evidentiary hearings.” This was wishful thinking. On large commercial loans, a difference of just 100 basis points in the interest rate can mean tens of millions of dollars in additional annual interest expense. If there is a cramdown fight, the risk premium is certain to be in dispute and it is hard to imagine a court adjudicating that issue without an evidentiary hearing and without expert testimony. The lower courts have articulated a large and expanding list of factors that can be considered in determining the risk premium, including: (1) the general circumstances of the estate; (2) the nature of the security; (3) the duration and feasibility of the reorganization plan, including adequacy of capital, earning power of the reorganized debtor, general economic conditions, and management’s ability and its probability of continuation; (4) the current and future state of the debtor’s operations; (5) any potential depreciation or appreciation of the collateral; (6) the size of any equity cushion; (7) the loan-to-value ratio; (8) the location, age, and condition of the collateral; (9) whether the local economy supports the particular type of development; (10) cash flow; and (11) the debt service coverage ratio. The point is that every debtor and every property is unique and the appropriate risk premium can be determined only by looking at the financial and operational circumstances of the particular debtor, comparing the collateral to other like properties to assess its particular risks, and comparing the general type of property to other asset categories (for example, the pickup truck in Till presumably would depreciate faster than a piece of commercial real estate).
What this all means is that there never will be an easy answer on cramdown interest rates. Every case will be different and every property within each case may be different. Defending or defeating a proposed cramdown rate in a plan of reorganization will require careful assessment of multiple factors, and there is no definitive guide to what evidence a court will find most persuasive. There is, however, a growing body of judicial decisions determining cramdown interest rates. We looked around and did not find any secondary source that provided a comprehensive review of the cases, so we went ahead and created one. Our Cramdown Matrix summarizes the results of all the reported cramdown decisions we could find.
More from the Bankruptcy Blog
Copyright © 2020 Weil, Gotshal & Manges LLP, All Rights Reserved. The contents of this website may contain attorney advertising under the laws of various states. Prior results do not guarantee a similar outcome. Weil, Gotshal & Manges LLP is headquartered in New York and has office locations in Beijing, Boston, Dallas, Frankfurt, Hong Kong, Houston, London, Miami, Munich, New York, Paris, Princeton, Shanghai, Silicon Valley, and Washington, D.C.