Using artificial neural networks to solve banks’ problems

Why should you care about banks?

Today, over 5 billion people worldwide have a bank account. People often turn to banks for financial stability and security. Banks protect your money for you and you don’t have to worry about hiding the money yourself and keeping it secure. Even if the bank you store your money in goes out of business, you won’t necessarily lose your money. The government insures your money that’s stored in banks so you will get your money back if a bank closes down (as long as you have less than $100,000 in your bank account).

Here’s an example of the money flow brought about by a bank

How do banks earn money?

Despite their association with the government, banks are private institutions. This means that in order to stay running, they need to earn money and make a profit. How do they accomplish this?

What could possibly go wrong?

In order to earn a profit, banks need customers to store their money in the banks. Then they can loan out this money and earn a profit on it. However, when people holding money with the bank want to withdraw their money, the bank needs to be able to give them what they want. They need to make sure that they don’t loan out so much money that there is nothing for the account holders when they want to withdraw.

How can we avoid this?

It's clearly not a good thing when banks go bankrupt on a largescale. When this happens, millions of people are harmed and the economy suffers. As we have seen, banks can often go bankrupt when many people want to withdraw all their money from a bank at the same time.

My project: creating the artificial neural network.

I decided to create my own artificial neural network to solve the problem described above. The goal of my ANN is to predict whether customers are likely to keep their money with a bank or leave a bank within the next six months given specific data points about customers. At this point, you may be wondering how exactly an ANN works and how I used one to solve this problem. Don’t worry, I’ll answer both of these questions.

What is an ANN?

An artificial neural network is a type of artificial intelligence that makes networks of “neurons” to analyze data and draw conclusions about different problems. Neural networks are made to model the human brain.

This is what an artificial neural network looks like.

Using ANNs to analyze bank customer data.

Despite now knowing what an ANN is, it might not be obvious how to make use of one in this specific case. Does this problem fit into the types of things that artificial neural networks can do? We need to predict whether customers will stay with or leave a bank based on certain data about them. In this case, we have definite data to feed into the neural network, and we are trying to predict something specific. Thus, we can make use of an artificial neural network to get the job done.

Implementation of the ANN

In this case, the neural network uses specific data about customers to make a prediction about them. Information about the customer’s country, age, bank balance, salary, and other such factors were used to make the predictions. The ANN trained on this data and tried to make correlations between this data and the likelihood of whether the customer would leave the bank. After making these correlations, the ANN was then trained and was able to make accurate predictions about the customers.

Checkout my ANN!

Key Takeaways

  • Banks provide financial stability and security to many people and they stimulate the economy.
  • Banks earn money by taking a small upcharge on the money they loan to people. This upcharge is known as interest.
  • Banks can get into trouble if they loan out too much money and customers want to withdraw money
  • We can use an artificial neural network to predict whether customers are likely to keep their money with a bank or withdraw their money and leave a bank. This would help banks out as they would be able to determine how much money they should be loaning out.
  • ANNs are algorithms that attempt to simulate the function of the human brain to make correlations between data points and make predictions. We can use them, in this case, to help out banks.

Wait… don’t click away yet!

I’m Adam, a 16 year old passionate in technologies like artificial intelligence/machine learning, blockchain, quantum computing, and much more.



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