AI, also known as machine intelligence, is all about creating machines that demonstrate the intelligence that is usually displayed by humans in the form of natural intelligence. John McCarthy coined the termartificial intelligence in 1955.

AI has witnessed two winters so far: once in the 1970s with the reduction of funding by the Defense Advanced Research Projects Agency or DARPA (https://www.darpa.mil/), then known as ARPA, and another time with the abandonment of an expert system by major IT corporates such as Texas Instruments (http://www.ti.com/) and Xerox (https://www.xerox.com/).

In a way, AI aids in the process of transferring decision making from humans to machines, based on predefined rules. In the field of computer science, AI is also defined as the study of intelligent agents. An intelligent agent is any device that learns from the environment and makes decisions based on what it has learned to maximize the probability of achieving its predefined...

The banking sector is defined as a devoted economy for holding specific types of financial assets using methods that will make said assets grow financially over a period of time. Banking sectors are governed by rules imposed by governments or similar bodies.

Renowned author and financial consultantStephen Valdez described in his work, Introduction to Global Financial Markets (please visit https://www.macmillanihe.com/companion/Valdez-Introduction-To-Global-Financial-Markets-8th-Edition/about-this-book/), the different types of banking in the global financial markets. These are commercial banking, investment banking, securities firms, asset management, insurance, and shadow banking.

These types of banking are required to fulfill the needs of a wide variety of customers, ranging from large organizations to individual customers. The following is a description of these various types of banking based on the needs of customers:

Like electricity and water, banking should be made as widely and easily available as utilities. Only when we make banks efficient can we make them accessible and have them benefit the highest number of people possible. Banking is a service that is provided to make the best use of capital/money to generate returns for those whosaveand/orthose who need the capital to have a more productive life at an agreed risk and return.

What we want to do is to be consistent with Robert J. Shiller's sentiment in his book,Finance and the Good Society, where he indicates the necessity of information technology in finance to help achieve our goals. A step further would be to leverage open source methods and applications to solve the accessibility challenges of the banking industry. Open source software solutions tend to be cost-effective, robust, and secure.

To make banking accessible, one of the most important things to do is to have a lot...

According to theMcKinsey Global Institute (https://www.mckinsey.com/~/media/mckinsey/industries/advanced%20electronics/our%20insights/how%20artificial%20intelligence%20can%20deliver%20real%20value%20to%20companies/mgi-artificial-intelligence-discussion-paper.ashx), outof 13 industries, financial services ranked third in AI adoption, followed by the high-tech, telecommunications, and automotive and assembly industries.

As theMckinsey report does not mention the use case in banking, with a bit of research, perhaps we can take a look at the four ways in which AI creates values, as shown in the following list:

• Project: Forecast and anticipate demand, improve sourcing, and reduce inventory (capital).
• Produce: Provide services at a lower cost or higher quality.
• Promote: Provide offers for the right price with the right message for the right customers at the right time.
• Provide: Rich, personal, and...

We began this chapter by explaining what AI is all about. AI is the technology that makes machines perform tasks that humans can do, such as weather prediction, budget forecasting, and more. It enables machines to learn based on data. We looked at the various techniques of AI, such as machine learning and deep learning. Later, we looked at the complex processes of the banking domain. If we can automate them, we can reduce costs in the banking sector. We also learned about the importance of accessible banking. Later, we looked at the application of AI in the banking sector and its positive impact, with a few numbers to support it.

In the next chapter, we will continue our journey of AI in banking. As a next step, the chapter will focus on time series analysis and forecasting. It will use various Python libraries, such as scikit-learn, to perform time series analysis. The chapter will also explain how to measure the accuracy of machine learning-based forecasting...