Game Theory in Action: Making the Deal Happen in Large and Complex Debt Restructurings (1/2)
By Ravindran Navaratnam (Sage 3)
The dynamics between borrowers and lenders in the context of debt restructuring can be simulated in the form of a strategic game, with players formulating various tactics to optimize their outcomes. To set the scene for this game, we identified the players, strategies, and payoffs, shedding light on the role of valuation and the associated critical values. This article explores the relationships between borrowers and lenders, focusing on the choices made in a debtor-in-possession restructuring and the outcome based on various scenarios.
The role of valuation and its application
Firstly, we set out the importance of valuation. Valuation plays a pivotal role in debt restructuring, influencing the decisions of both borrowers and lenders. Three essential values come into play: Force Sale Value (“FSV”), Market Value (“MV”), and Enterprise Value (“EV”). FSV represents the lowest value, where lenders recover only the tangible assets at a minimal price; a value associated with the disorderly disposal of the business’s assets. MV is normally the value of the tangible assets of the business realised with assistance from the borrower. This is in the context of orderly disposal which includes effort by the borrower related to asset maintenance and sales facilitation. We argue the moral obligation of a borrower is to assist lenders recover MV as a minimum. EV, or post-restructuring value, surpasses the MV, requiring the borrower's commitment to sustain new resources for continued business operations in our view is beyond any moral obligation. The EV is expected to be significantly greater than the MV, as today’s modern businesses’ value is substantially in its intangible value.
The simplified game and strategies
Next, we shall delve into the players and strategies. There are two (2) main players in the simplified game, namely the borrowers and lenders who are engaged in a debtor-in-possession restructuring to resolve financial distress. The borrower makes the first move by making an offer to settle the outstanding debt. Based on the above train of thought, the offers that borrowers can make are based with reference to more than or less than MV. The distribution of surplus to lenders above FSV is dependent on the lender’s legitimate power in loan documents and contributions of parties involved in terms of New Money & resources.
The borrower's choice to offer above or below MV shapes the strategies, and lenders respond with either acceptance or rejection. The abovementioned creates four strategies (each with distinct payoffs): (1) (Offer > MV, Lender Accepts); (2) (Offer > MV, Lender Rejects); (3) (Offer < MV, Lender Accepts); and (4) (Offer < MV, Lender Rejects).
The above strategies and representations of the game are in the context of liabilities exceeding the sustainable debt or even the EV thus, one could view a debt settlement as a borrower buying back the business from the lenders; the de facto owner.
The payoff
The third component of the game will be the pay-off analysis. The payoff matrix illustrates the outcomes for different strategies. The dynamics change when the offer is above or below MV, creating winning and losing outcomes depending on acceptance or rejection. Noteworthy, lenders are caught in a predicament between their desire for higher recoveries and the fear of establishing a problematic precedent through debt waivers, which could potentially give rise to moral hazards. They worry that even financially stable borrowers might intentionally default to reap the benefits of restructuring. Therefore, if they have a reason to believe that borrowers are disingenuous in their offer, then liquidating the borrower is considered to be a positive outcome. This aligns with the bank’s strategy of profit maximization, which emphasizes support only for responsible borrowers.
The table below provides a summary of the payoff with reference to examples and context in the real world in the form of four (4) scenarios.
|
Lender |
|
Borrower |
Accept |
Reject |
EV > Offer > MV |
Win, WinScenario1 |
Lose, LoseScenario3 |
MV > Offer > FSV |
Win, loseScenario2 |
Lose, WinScenario4 |
The first observation from the table above is that there is no dominant strategy for either player.
Scenario 1
Achieves a win-win by borrower offering above MV, so long as it is not an unreasonable offer i.e. with settlement terms where the debt is unsustainable and at the expense of New Money. The latter should not be a concern if the New Money understands the Enterprise Value and their effective post-restructuring control of the equity capital of the business. Practitioners understand a win-win, emphasizing higher recovery value in restructuring and preserving the business’ going concern value. From the game theory perspective this is a Nash equilibrium as the borrower makes an offer over MV, where the lender has no better strategy but to accept. Similarly, if the lender is expected to accept there is no better strategy for the borrower than to make an offer above MV.
Scenario 2
Despite a below-market offer, the lender favours debtor-in-possession resolution and this could be explained by the Lender taking a cooperative stance or being naïve!
Scenario 3
This is an erroneous decision by lenders and a reasonable Lender is willing to correct a wrongly rejected above-market offer if the borrower makes a compelling argument and/or there is a path for escalation to enable an amicable resolution. Undoubtedly credibility and trust play an important role.
Scenario 4
The lender exercises creditor rights and becomes indifferent. Lenders prefer liquidation to teach the borrower a lesson in a scenario with below-market offers, where liquidation is preferred despite the lower recovery in financial terms. In this instance the borrower recovers no amount of his capital. This is the second equilibrium if the borrower makes an offer below MV, the lender has no better strategy but to reject. Similarly, if the lender is expected to reject there is no better strategy for the borrower than to make an offer below MV. Therefore, challenges exist in moving from liquidation to restructuring due to entrenched positions and trust issues.
The debt resolution should be understood in terms of Nash equilibria; without such equilibria, borrowers and lenders would be incentivized to deviate, thereby disrupting stability. In the game one Nash equilibrium establishes a case for restructuring the other liquidation. Noteworthy, prediction about a strategic situation must establish a Nash equilibrium to be considered credible, with the equilibrium ensuring each participant's optimal response to the others. In essence, Nash equilibria underpin the structure, proposal for behaviour, and theoretical forecasts within debt restructuring contexts.
Application of business economics
This paper clearly sets out a case for borrowers to be reasonable and to offer debt settlement to lenders above MV achieving a debt resolution rather than face liquidation. In the next paper of this series, we shall discuss the implications for the lender’s decision and in particular the loan recovery officers arising from the perspective of impairment that lenders make on the carrying value of the loan. This revolves around the concept derived from the “policy game”. There are three (3) main scenarios for the lenders that come into play, first low impairment, followed by high impairment and lastly perfect impairment on the loans.
We are of the view that various policy initiatives with respect to listing rules, banking regulation and taxation could encourage debt restructuring. However, these are difficult to implement without a strong political will. Thus, it is worthwhile to explore the different nudge techniques which may enable restructuring. We shall discuss encouraging restructuring based on ideas with respect to both policy initiatives and nudges in future articles in the series of “Making the Deal Happen in Large Complex Restructurings”.
* The author would like to express his sincere thanks to Professor Lim, Woo Young of HKUST for providing guidance and exceptional teaching on game theory. The author would also like to thank his staff at Sage 3, Durra Qistina Shaiful Bahari, for her support in helping him write the paper and for her keen interest in game theory.