As a third-year student of IT with a parallel interest in business and investments, I have become fascinated by the study of machine learning trends in various sectors of the industry. Among these, the banking sector stands out as a particularly amazing area, where machine learning is not merely an innovative tool, but a revolutionary force reshaping the very fabric of financial services. In this blog post, we will be exploring the latest trends in machine learning in the banking industry. Join me as we uncover how the unification of these two fields is shaping the future of financial services.

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How well do we know AI?

I first discovered machine learning during my second year of studying, and I have been passionately using it throughout my major studies. I became acquainted with fundamental concepts such as decision trees, classification and logistic regression, as well as more complex algorithms like random forest and convolutional neural networks. My interest in exploring industrial solutions was ignited after participating in case competitions. A case competition is a team event where participants are tasked with devising a solution for a real-world business challenge presented by a company.

Machine learning technology is all around us and has become an integral part of our lives. Your recommendations on YouTube, playlists on Spotify, and even suggestions on a marketplace are all powered by machine learning. But what if I told you that banks are also embracing artificial intelligence (AI) technologies? Your credit cards are smarter than they seem. They help analyze your purchases and offer personalized offers. The products on the bank’s website that seem perfectly tailored for you don’t just magically appear on the homepage. The site analyzes your previous internet activity using information from your internet provider and cookies, then presents an offer especially for you. Even a bank's chatbot is powered by AI and operates thanks to machine learning.

Trends in banking AI

Further, let’s consider some of the most popular applications of machine learning in the banking industry. We can highlight credit risk assessment, where a model analyzes a person’s creditworthiness to determine whether to issue them a loan or not. While this technology has the potential to be very beneficial, there are some legal restrictions that need to be considered. Also of interest are technologies for automating document workflows, algorithms calculating the effectiveness of specific strategies, and applications of machine learning to predict changes in the stock market. However, these technologies are internal components of a bank, not directly impacting regular customers. Personally, I find technologies that have a direct impact on the user experience the most interesting. In particular, algorithms that provide personalized recommendations on banking websites and mobile applications, as well as chatbots that assist users in support conversations.

My experience

I participated in the CUP IT 2024 Case Championship. As part of the championship, we were tasked with proposing solutions to improve website personalization at Alpha Bank, one of the largest banks in Russia. While working on this task, we analyzed a significant amount of statistics and identified some interesting approaches among the existing ones. We found that banks are major investors in artificial intelligence and a significant amount of resources is devoted to content personalization algorithms and user behavior analysis. Additionally, there is a wealth of evidence showing that users greatly value the presence of chatbots powered by AI.

What does it all mean for us?

To summarize, let me draw some conclusions from the points I've made so far. Firstly, I hope that after reading this article, you've gained a better understanding of why banks and other companies seem to be able to predict your thoughts. Whether for better or for worse, there is no magic involved. It's simply thanks to machine learning algorithms and artificial intelligence. Secondly, I aimed to show how machine learning is permeating every aspect of our lives in unexpected ways. As we can see, machine learning algorithms are evolving rapidly. Their scope of application is expanding, and they are becoming an integral part of our daily lives. Additionally, there has been a significant increase in investment in artificial intelligence, according to Forbes magazine. It's being used by almost all major players in the industry, and it's clear that this trend will only continue. Finally, considering the significant investments and impressive results, AI will continue to play an increasingly important role in our daily lives.