Summary

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. The chapter will be full of interesting content and will teach you how to combine financial ratios with machine learning models. This will provide a more in-depth look into how machine learning models can be applied to solve banking problems.