Applied AI in Fintech: Predictive Risk & RegTech Systems

Welcome to Applied AI in Fintech: Predictive Risk & RegTech Systems. If you want to understand how artificial intelligence risks in cybersecurity and machine learning are actually used in the real world of finance today, you are in the right place.

In this course, we start by looking at why AI has become so important in finance. Financial decisions should never be based on human emotion. They need to be backed by hard facts, fast data processing, and objective rules. By learning how to use these modern algorithms, you can help financial institutions reduce costs, increase transaction speeds, and make much smarter lending and investment choices.

We believe the best way to learn is by doing. You will start by looking at real financial data, like the famous German Credit Dataset, to see how we clean and prepare information so a computer can understand it. From there, we will explore practical machine learning models. You will learn how to build systems that automatically predict credit default risk using simple regression and decision trees.

Once you understand the basics, we will dive into deep learning. You will see how artificial neural networks are built to mimic the human brain, allowing computers to find hidden patterns in massive amounts of financial data.

Finally, because the financial world is heavily regulated, we will look at the big picture. You will learn about RegTech and SupTech, which show how regulators use AI themselves. We will also discuss the ethical side of AI, and how relying too much on automated machines can sometimes cause systemic risks in the market.

By the end of this course, you will have a clear, practical understanding of how to build AI models for finance, and how to use them safely and ethically.