11.01.2017

# Clash of Maths and Law: Introduction to a Mathematical Strategy for Innovative Alternative Dispute Resolution

I recently attended a German Legal Tech Meetup. During a discussion, an in-house lawyer asked if there was a technical solution to the following problem (personal experience):

#### I. Problem Description

Complex post-M&A disputes have never been subject to a court’s decision. The parties have always concluded their case by way of a 50/50 split settlement after many years of dispute, which have led to an astronomical increase in costs. There is no indication that this situation will change.

The group was not able to answer the question except for highlighting the necessity of a (rather improbable) first post-M&A decision by the German Federal Court of Justice. So I took the floor and answered:

If you have such unambiguous experience and know that the parties will settle by way of a 50/50 split, why don’t you endeavor to reach an amicable agreement equivalent to this prior to a lawsuit, saving court’s and attorneys’ fees? You do not need any information technology in order to save time and costs.

The group reacted with anger, especially the in-house lawyer who cried out: Then we must not enter into contracts anymore!

#### II. Analysis

Stop.
Rewind.
What went wrong? Why did the group react like this?

Did the lawyers react with anxiety substituted by anger? I assume they did not, because it is the implementation of Legal Tech and Artificial Intelligence that triggers the fear of becoming obsolete, not a simple tech-free strategy based on the calculation of probabilities (and the ability to learn from the results of bad decisions).

Did I cut the ground from under the litigation lawyers’ feet, who have a clear interest in accompany-ing complex post-M&A disputes? Presumably not. We were the only two litigation lawyers attending the meeting and my litigation colleague was the only one to endorse my statement later on.

Then why did the in-house lawyer react with disgust? This person, who raised the question of how to save costs in complex disputes that “never” result in a court’s decision, but “always” in a 50/50 split settlement, reacted in the most unfriendly way.

Well, there is a psychologically and sociologically reasonable ground for this reaction: the in-house lawyer was driven by the idea that an extra-judicial initiative to settle by way of a 50/50 split deprives either party of the (admittedly very slight) chance to win the upcoming lawsuit.

The other participants might have had the same thoughts.

#### III. Adding a dash of reality

The in-house lawyer referred to a personal experience which is absolutely consistent with reality:

According to a study conducted by Baker (&) McKenzie and Alvarez & Marsal in 2013 and 2014 more than 90 per cent of post-M&A disputes are settled amicably (pages 5 and 19). While public court proceed-ings are cheaper than arbitration, arbitral tribunals offer a greater understanding of mergers and acquisitions and a shorter duration of proceedings (page 5). However, both procedures face inefficiencies due to the complexity of post-M&A disputes (page 5).

50 per cent of post-M&A claims are realized on average - by both settlement and decision (page 19). As it achieves the same outcome, but with a shorter duration and reduced court and attorneys’ fees, settling a post-M&A dispute is the more efficient solution.

Considering the cost-efficiency of settlement agreements highlighted above, the question arises as to why extra-judicial settlement agreements are not taken into account when seeking the most efficient way to settle a dispute. The study points out that the costs of proceedings constitute an impediment to pursuing a claim (page 19). An extrajudicial settlement by way of 50/50 split excludes both court and rocketing attorneys’ fees.

To sum up, both the in-house lawyer's experience and the post-M&A disputes study imply that there is a real need for an innovative alternative dispute resolution strategy.

How could this need be satisfied?

#### IV. Game changer game theory?

A post-M&A dispute between two parties could be simplified as follows: party A claims EUR 1 billion. Party B rejects A’s claim. The case is highly complex and has not been taken to court yet. Both parties turn to their General Counsels and discuss how to proceed.

Both General Counsels know that there is a very high, an approximately 90 per cent probability of settling the case at EUR 500 million. Of the remaining 10 percent there is either a 50 per cent chance to win or lose. Will the other party fight or cooperate in order to save time and costs, knowing that there is only a slight chance of winning, while costs skyrocket?

The corresponding in-house lawyer’s experience, reaction and study named above show that dis-putes are taken to court because there is a chance to win, notwithstanding the immanent high risk of loss and costs. Accordingly, each party has to assume the other party will fight in order to win. There is no chance of settling the dispute if one party refuses to cooperate. Ultimately, no party is willing to initiate settlement negotiations.

However, the will to cooperate increases with the passing of time and accrued costs (and pressure exerted by judges or tribunal).

The parties find themselves in a dilemma situation. It might remind you of the mathematical problem called the 'Prisoner's Dilemma’, a subset of game theory:

The prisoner's dilemma describes a situation in which two parties led by their own self-interest make a decision that does not result in the desired outcome. Typically, both parties choose to bene-fit at the expense of the other party. By following a self-serving and logical thought process, both parties end up in a worse situation than if they had cooperated with each other.

Cooperation instead results in a sum of strategies, which prevent a worse outcome considering the other party’s choice. The so-called Nash Equilibrium describes the optimal combination of game strategies where no player has an incentive to deviate from the chosen strategy.

#### V. Profitable cooperation

What is the optimal combination of strategies in post-M&A disputes where no party has an incentive to deviate from the chosen strategy? Working towards an extrajudicial 50/50 settlement. Pursuing victory results in financial loss, even if the parties settle before the court. The chance of winning is too slight to be considered a realistic chance. Early cooperation is the most profitable strategy.

#### VI. Legal Tech solution for determination of the best cooperation strategies

The need for an innovative post-M&A alternative dispute resolution strategy has been identified. The optimal combination of strategies is early, extra-judicial cooperation with the goal of agreeing on a 50/50 claim split. One question remains though:

Is Legal Tech able to support the cooperation process?

Unfortunately, there will be no Legal Tech solution for changing a party's mind if they are convinced they will win a dispute against all odds. Current Legal Tech solutions cannot replace a good lawyer's advice, but could help to identify the relevant transaction documents in order to accelerate the set-tlement process (e.g. e-discovery). Thinking of cooperation platforms, Legal Tech also allows for a closer and efficient cooperation between clients, lawyers, experts and other professionals regard-less of their places of business.

If parties to mergers and acquisitions realize that they blunder into a dispute, they should look for professional support in finding the best cooperation strategy instead of gambling. The support ser-vice should include enabling the parties to compare their realistic options and identify the best solu-tion to their case. Legal Tech will help to simplify the process and reduce stress for the parties involved. It will not be one product, but a smart combination of different, case-adjusted technical solutions.

The cooperation initiative nashgotiation.org wants to offer such alternative dispute resolution services to parties involved in complex disputes. Stay tuned.

Claudia Otto, COT Legal

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