From customer service to fraud detection and risk management, artificial intelligence has transformed the ways modern banks operate. Artificial intelligence applications in banking are now going beyond automation and data analysis, and the revolutionary use cases we will discuss in this article will prove it. Let’s discover the most exciting examples of artificial intelligence in banking and finance that are believed to be the future of this industry.
5 Ways AI Is Changing the Banking Industry
The role of artificial intelligence in banking has grown significantly in recent years. What’s more, it is expected to grow further—the global value of AI in banking is projected to reach $64 billion by 2030, compared to only $3.8 billion in 2020. So, what are the most prominent examples of artificial intelligence in banking that shape the industry’s future and drive its growth? Let’s consider them all in this section! By the way, if you also want to create a fintech project leveraging innovative technology, opt for our artificial intelligence development services right now!
1. Generative AI
Artificial intelligence in banking isn’t actually a new technology. It has been here for several years already, helping financial institutions with data analysis, customer service, fraud detection, legal compliance, automation, and product personalization. However, in 2023, ChatGPT became a game changer that is expected to revolutionize the financial sphere forever. The matter is that the world has never seen such a powerful deep learning model before. ChatGPT has 175 billion parameters, making it the largest language model available for use to date.
It means that while the core use cases of AI in the banking industry aren’t going to change much, the use of the ChatGPT model promises to make them more effective. For example, with its help, banks may rely on data with a higher level of confidence when issuing a loan. Since it is also capable of self-training, the accuracy of its conclusions is extremely high, and this is also why ChatGPT is believed to be the future of deep learning. What’s more, if you also want to power your next project with deep learning technology, you are welcome to contact us for help.
Getting back to ChatGPT, it is also going to make financial products recommendations and customer service hyper-personalized, especially with open banking on the rise.
As far as you know, open banking is the fintech concept, according to which customers’ data is securely shared between financial institutions using APIs, with the goal of conducting deeper customer data analysis and providing more relevant product recommendations. By enabling banks to access customer data from various sources and provide a more complete picture of their financial situation, open banking can improve the ability of ChatGPT to provide highly personalized services.
2. Smart and AI-powered Banks
“The number one bank in the world will be a technology company,” as Brett King, Fintech influencer, author, and futurist, predicted. In 2023, it doesn’t sound like a science fiction idea anymore. Instead, it is a reality we are facing today, with artificial intelligence in the banking industry’s spotlight.
In 2022, 57% of Millennials were extremely interested in switching to digital-only banks, mainly because of the advanced personalization they can promise, so it would be safe to predict that AI-powered banks will soon replace traditional ones. One example of the smartest bank existing now is Ally Bank, which offers a fully digital experience and uses artificial intelligence to provide personalized recommendations to customers.
In addition to more individualized service, smart banks can offer a more consistent digital experience, sentiment analysis, financial necessities’ prediction, more efficient operations, and upgraded security systems based on blockchain. The most advanced smart banks are also believed to leverage augmented reality to provide virtual in-branch tours. It can also be used for the financial education of the customers. With the help of AR, banks can create engaging tutorials explaining to users the specifics of investment or stock management.
The latter, in turn, is another promising technology that shapes the future of the banking industry, taking finance and data safety to the next level. So, if you are also contemplating creating a fintech software solution that will be based on blockchain, we, at Litslink, would be happy to share our latest expertise and best practices in both AI and blockchain development!
3. Conversational Banking
Conversational banking is a rapidly growing trend that is transforming the way banks interact with customers. This technology is also believed to be the future of artificial intelligence in banking, since AI virtual agents take customer service to the next level and make things much easier for users. Some of the most famous examples of conversational artificial intelligence in the banking system include Bank of America’s Erica, Capital One’s Eno, and Ally Bank’s Ally Assist, with their features going beyond natural language processing.
For example, in addition to account management, bill payment, and fraud detection, Erica conversational chatbot provides proactive insights that help users manage their finances. Spend Path insights help customers understand their spending patterns and optimize their budgets accordingly. Ally Bank’s assistant, in turn, can be integrated with other solutions, like Amazon’s Alexa, which makes it an exciting example of how the use of artificial intelligence in banking can be coupled with smart home technologies.
4. In-branch Banking Robots
In-branch banking robots are one of the most exciting applications of artificial intelligence in the banking industry. Banks are increasingly using them to enhance the customer experience and improve operational efficiency. These robots are designed to perform a variety of tasks.
For example, Pepper, a robot created by SoftBank Robotics, has found use in various banks worldwide, including HSBC, Mizuho Bank, and Bank of Tokyo-Mitsubishi UFJ. Its purpose is to welcome customers, answer simple queries, and provide information on bank services and products.
Another robot, called Connie, was originally developed by Hilton Hotels but has been adapted for use in banks like Capital One’s Union Square branch in New York. Connie’s primary function is to offer clients personalized recommendations and details about bank products and services, using artificial intelligence to learn about their preferences and provide tailored suggestions. Finally, the National Australia Bank (NAB) has installed SoftBank Robotics’ NAO robot in some of its branches. NAO is also capable of performing transactions such as opening accounts and transferring money.
5. The Bank of Things
The global Internet of Things (IoT) in banking market size was valued at $12.7 billion in 2021 and is projected to reach $237.4 billion by 2031. The benefits of artificial intelligence in banking become even more significant when this technology is coupled with IoT, and such a combination noticeably diversifies the use cases of both innovations.
For example, some banks have already implemented smart ATMs that use sensors and connectivity to provide a more personalized and secure experience to users. Usually, such ATMs are also equipped with surveillance and fraud prevention features, like face and voice recognition, or identity detection.
In China, which is known for its specific attitude to public safety, using surveillance cameras in banking is a norm. These devices are equipped with face recognition and data analysis technology, so they are used for monitoring entry and exit points, identifying employees and customers when they open a new account, withdraw a certain amount of cash, or apply for a loan. While the usage of these technologies raised concerns about data privacy, they still showcased themselves as effective solutions for fraud prevention.
The importance of artificial intelligence in banking grows even more when it comes to preventing money laundering with the help of AI and IoT. For example, AI-powered surveillance cameras can help with money laundering by providing evidence of suspicious activities and transactions. For example, some banks use them to monitor customers’ and employees’ behavior and identify patterns of activity that may indicate this kind of crime.
Conclusion
In 2023, the applications of artificial intelligence in finance and banking go beyond routine tasks automation. From fraud detection and prevention to personalized customer service, AI has provided banks with powerful tools to improve efficiency, reduce costs, and enhance the customer experience. That’s why more and more banks are expected to adopt AI technologies in the near future, transforming the ways we manage our finances, make investments and savings, and interact with financial institutions.
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