What is the rationale behind the eyes of the poor?

Microcredit supporting women in rural India


Every adult in the modern world has had an interaction with the bank. The bank is a financial epicenter in cash flow in our society. Every person, in this society, has taken out a loan for a cardinal reason. Whether it be to pay for a house, a car, credit card debt, etc., loans are a hallmark to keep the needs and wants stable in a person’s life. However, with a large percentage of the population of India living under $3 USD PPP, the same rules do not apply. The poor, mainly concentrated in rural parts of India, do not have the same institutions as the ones who are less poor. This concern is not one of lack of access to financial institutions but rather a high maintenance cost for the loan officer. Although the poor would ask for a small loan, a well-known bank would not lend as enforcing a contract would have a higher percentage of cost in the loan provided. This brought a new financial institution specifically targeted to the poor: microcredit system. Microfinance institutions are one of the pillars that keep India upright, such as companies like Spandana providing excellent support for poor people all over India. Microcredit is of great importance as it allows for realistic payable loans for the poor, especially women so that they can start a small business or sustain their current living. 

Game Theory

Game theory allows us to analyze the interactions between people, in terms of utils, to effectively understand the intended rational outcome that is best for all parties. Game theory provides us the necessary tools and analysis to effectively conclude a result of a game. The solutions to the game are equilibria that tell us the best outcomes for both parties in terms of the utility function of the players. There are two tools of great importance: Pareto Optimality, and Nash equilibrium. Pareto optimality is defined as the outcome of best interest is the maximum utility of both players. 

Player 1’s utility is the x axis and Player 2’s utility is in the y axis

 However, the Nash equilibrium gives us the outcomes that are calculated by finding the best action that a player takes given a player chooses a different action, and this does not necessarily translate to an outcome that has the maximum utility for all players. 

Although both tools are vital to understanding a scenario, they do come with some crucial assumptions that are hard to neglect. The first assumption is that all players are rational, meaning that players will always choose an action that has a higher utility. In a game, it is tough to look away from this as an irrational decision can exploit the rational behavior of the opponent. Another critical assumption is that the utility model accurately portrays the needs and wants of the players. The outcomes resulting from our actions can make sense subjectively, but quantifying these can come with some discrepancies when not carefully understanding the situation thoroughly.      


The Players in this game are the loan seeker (the civilian), and the loan officer.  To keep it simple, the civilian can ask for a loan for three reasons: to meet the daily requirement to stay alive, to set up a shop, or to start a company.  The loan officer has four options: provide a small loan with an interest rate over a long or short term, or give a large loan with an interest rate over a long or short term.  The actions for each action can be analyzed in a matrix.  When constructing the matrix, the default rate, the purpose of loan were the primary consideration in rating the ulitiy. The scale of the utility for both players range from 0 to 10, where 5 utils would be considered indifferent.


Actions of loan officer






Actions of civilian

















SLLT: Small oan, long term; SLST: Small loan, short term; LLLT: Large loan, long term; LLST: Large loan, short term

DR: Daily Requirement; SS: Small Shop; C: Company (expanding inventory or chain restaurants)

Nash Equilibrium : (DR,SLST), and (C,LLLT)

Pareto optimality: (C,LLLT), (DR, SLLT)

In conclusion, the nash equilibrium makes a more appropriate conclusion as the civilian would most likely want a small loan for a short term for daily requirements.  The civilian would not want to pay a loan for a long time for something that is very essential and the money spent over that long time could be spent on something else, like saving for education or a bad situation.  The other equilibrium also makes sense as a company would most likely want a large loan payed over a large period, as it would be difficult to pay in a short period.  This equilibrium shows that trust between the civilian and the loan officer as both have a high utility.  This conclusion of trust is further backed by the pareto optimality technique as this outcome is a pareto optimal.

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  1. April 26, 2020 by Shari Abbott

    Harish-what an interesting application of your concepts to a context that is relatively well known to me. The personal experiences that prompted your choice of this topic was clearly conveyed in your intro. video, and I was curious about the specifics relating to whom you mentioned were the microlending recipients. I have some understanding, living here in Chennai with you, and I wonder if others could have used more specifics. Additionally, I appreciate your clear graphs of game theory. Since I have no prior knowledge, I wasn’t sure if you concluded the the Nash Equilibrium was of higher utility in this context, and how strong the utility was for the Pareto Optimality. Both were very interesting to examine. Finally, as your former English teacher, I wish you had proofread your capitalizations and punctuation.

  2. April 26, 2020 by Pranav Unni

    Harish, the topic of loans is something very interesting and something that I know a bit about having lived in India for the past 6-7 years. I think that your video helped me understand the overall basis of the project and the reason/fuel for why you wanted to do it. The visual representations are very useful in understanding the page. The graphs are very clear and help me understand the project better. Great job Harish!

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