Game Theory Can Teach Bankers How to Be Smarter Negotiators

“The most powerful weapon in chess is to have the next move.” -David Bronstein, chess world finalist

Facing off with a vendor to negotiate a multi-year contract is much like a game of chess. Move after move, decisions are made based on information available at the time. Contract negotiations typically have two players, each applying their strategy to obtain desired terms, conditions and pricing. Neither party is ever completely certain of their opponent’s next decision, but both are likely experienced enough to predict potential moves.

Game theory is an economics framework that provides decision-makers with a method to analyze their strategies while considering how the decisions of others will impact the outcome. Contract negotiations between financial institutions and their technology vendors are an ideal application of game theory. Each party seeks to maximize its outcome while considering the other party’s actions.

Compare a contract negotiation to dividing up a pie. Both parties want to keep a greater share of the pie. A deal based on a zero-sum game, where the result is an advantage for one side and an equivalent loss for the other, will never work in this scenario. Unrealistic demands or lowball offers from either side of the table fall into this category and can destroy the professional relationship.

Game theory, on the other hand, suggests that both parties know what their share of the pie should be based on all available information. This is especially true when the two parties have a close working history.

Game theory provides negotiators with an efficient framework in which to apply their strategy. In game theory, a decision-maker (negotiator) bases their decisions on what the other player is thinking. This requires them to map out the order of likely choices, which can occur sequentially or simultaneously. Sequential games are played in turns, with each player executing a decision following a previous decision by the other player.

Contract negotiations between a financial institution and a vendor are performed sequentially and follow a decision tree, also known as a game tree. Constructed with the end result in mind, the game tree is built from the bottom (the final decision) to the top (the initial offer) and maps out each player’s decisions and expected benefits.

Consider an example of a core system renewal where the financial institution has information that a renewal price should be $750K. The financial institution understands the game before it even happens. It knows the ideal outcome and the possible decisions to get there. A simple illustration of such a game tree is below (actual negotiations have more branches and can grow more complex):

The financial institution maps out the decisions, and while it offers $700K, it is planning on a final agreement of $750K for the contract. The informed financial institution has high confidence the vendor will counter with $750K. This expectation is based on reliable pricing information and industry knowledge before the initial offer is presented. This efficient process avoids wasted effort with lowball offers, and the vendor likewise avoids unrealistic counteroffers.

The pricing and industry knowledge is referred to as “perfect information” in game theory. Information is essential, but perfect information for both parties would equate to collusion (we assume that does not occur). Contract negotiations operate in a world of available information to effectively negotiate.

The challenge for many financial institutions is knowing the market price for the negotiation they are conducting. Effective negotiators seek to deliver the best outcomes with the information available and to map out the likely scenarios at each decision point to create a winning plan. Better information results in improved outcomes.

There are a few key actions financial institutions can take to improve their negotiating game:

1. Make the first move. The player who makes the first move generally has the advantage in sequential games. Financial institutions improve their outcomes by setting the pace.
2. Start with the end in mind. By mapping out the optimal decision strategy, the smarter bank seeks to obtain the best outcome given the potential decisions along the path and their expected payouts (i.e. benefits). To achieve this, the institution needs accurate information regarding the vendor, pricing and industry trends.
3. Watch the time. An environment to support optimal decision-making should not occur under a time crunch. The smarter bank ensures it can be patient. Your opponent can take advantage of your impatience when you are under a time constraint. Positioning the organization into a take-or-leave-it scenario will change the outcome of the game.

John Nash, a major contributor to game theory, was one of the recipients of the 1994 Nobel Prize in Economics and was the focus of the biographical film, “A Beautiful Mind.” Nash has transformed negotiations by demonstrating how both parties win because they each achieve the outcome they desire. Nash illustrated how negotiation is about creating and obtaining value, but in the absence of reliable information, suboptimal decisions will occur.

Negotiations require proper planning, what-if analysis and the effective use of specialized data. Smarter banks that demonstrate this behavior can achieve optimal results. It is time for more banks to get a bit smarter about negotiations.

Game on!

Thanks to Brandon Miller, assistant professor of teaching in finance and economics at the University of Findlay, College of Business, for his contributions to this article.

Glenn Grossman is director of research at Cornerstone Advisors. Follow Glenn on LinkedIn.