Friday, October 10, 2014

Market Mechanic Lecture: Credit (Loans)

Board game designers have to decide when they provide credit in a board game if that credit is issued by a person (credit mechanic) or if credit is issued by an algorithm in the rules (credit theme).  Both techniques have different challenges to make them work within a board game.  To better build a board game mechanic or theme I am first going to see how both concepts fare in the real world.

Lenders in the Real World:

In the real world lenders gauge the riskiness of their investment in order to protect their money.  If a real world lender thinks a business plan has a higher probability of failing it will find compensating factors to either increase its reward if you succeed (higher interest rates) or provide compensation if you fail (higher collateral requirements).  While not always successful, lenders will take time to supervise their investments to make sure they did not get duped into some sort of ponzi scheme.  The incentive to protect their money from bad investments results in bankers vetting the people and businesses they extend credit to.

Real world lenders are always open to opportunities to make more money.  At first, this might sound like stating the obvious, but this statement has a big implication in lending behavior.  This means that if a lender discovers someone with a good business plan, even if the person asking for credit is not rich, does not have a long credit history, or is already holding some debt, the lenders is still willing to extend credit.  Credit in the real world is about seizing opportunities to make money and assessments are made based on the likelihood of the projects success.  

Challenge for Lenders in Board Game:

The advantage lenders have in the real world is that everyone benefits from making more money.  In a board game with a lending mechanic, game designers have to worry if any credit will be exchanged whatsoever because players may purposefully default to damage the lender in the game.  Even if players were not worried about a strategic default to take down the lender, lenders may not be willing to loan other players money because that might result in the borrower becoming stronger than the lender.

Michael R. Keller address this issue in his game Frozen Concentrated Orange Juice by having lenders and borrowers play two different games at the same time that interact with each other.  In one corner borrowers are competing with each other to be the best producers of goods.  In the other corner, lenders are competing with each other to be the best at extending credit.  By separating the borrowers and lenders into their own sub games, lenders and borrowers no longer have to worry they are engaging in a direct deal with their opponent that will undermine their chance to win the game. Borrowers do not reduce their chance of winning the game when the person who loaned them money does well and lenders are not hurt when the person who borrowed money from them does well.  

This separation allows Frozen Concentrated Orange Juice to enjoy the benefits of a loan mechanic.  Lenders will adjust their offers to borrowers in response to their credit risk.  They will monitor the investment decisions of borrowers and extend credit to borrowers who have good business plans.

Algorithms in Real World:

Real world credit, like board game themes, also use algorithms to issue credit.  Credit scores result in some lenders automatically offering individuals a credit line. Meanwhile, pawn and car title loan shops will happily issue anyone a loan using an algorithm based on the value of the collateral.  

Algorithms are a way real world lenders can reduce the cost and time to asses the risk of extending credit.  Credit scores allow lenders to look at a single number instead of talking to everyone who has information on the borrower.  The reliability of the scores let lenders get rid of costly employees and replace them with computer algorithms to automatically assigned credit lines to people with specific credit scores.

Pawn shops and title loans utilize an algorithm based on collateral to reduce the cost and time of assessing borrowers risk.   Instead of taking the time to track down the borrower's credit history, they take on the easier task of assessing the value of the items being pawned.  Imagine you walk into the pawn shop with 2 pounds of gold and you ask for a loan equal to 80% of the value of the gold.  The pawn shop owners can spend countless hours talking to your friends, your employer, and past creditors or, they can look up the current price of gold and say, if you do not pay back your loan the pawn shop keeps the gold.  Assessing the value of the collateral is an algorithmic approach to loans that takes much less work than assessing the worthiness of the borrower.  This enables the pawn shop to issue loans at a relatively fast pace and extend credit to a wider swath of people.   

Challenge of Algorithms in Board Games:

Algorithms (aka credit themes) in board games face two challenges that do not exist in the real world.  First, in the real world, if someone has a good business plan that does not fit into a pre-existing algorithm, they can pitch their plan to lender who has the discretion to offer them credit.  In the game of Monopoly, you cannot tell the bank that if it lent you the money to build the hotels on Park Avenue and Boardwalk that you would win the game.  Your credit opportunities are completely constrained by the algorithms followed by the bank.

Second, board games with a credit theme, unlike the real world, cannot alter its algorithms in response to new information.  If a player finds a loophole in a board game algorithm that lets them run a ponzi scheme then there is no adjustment to stop them.  If a person in the real world found a way to run a ponzi scheme due to a loophole in an algorithm then lenders would change the algorithm to protect themselves from future exploits.

That said, properly designed credit themes have one big advantage on credit mechanics.  Algorithms ensure credit will be extended to players playing the same game, even if credit gives one player an edge over another.  Algorithms are automatic, and potentially available to everyone.  As long as players meet the correct conditions they will have access to credit and be able to use credit gain an edge on other players.

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