AI for Banks and Fintech Companies

The capabilities of artificial intelligence (AI) may be a bit exaggerated in some spheres of life but its use in banking and financial technologies is fully justified. Moreover, banking is one of the most promising spheres for the use of AI.

Below we describe how AI is already used by banks and Fintech companies. In addition, we discuss some legal issues that arise in connection with the use of AI in banking.

The bank customer does not usually see the process where AI is involved. Analysis of the clients, their transactions, their requests, their behaviors – new technologies are actively employed in solving these tasks. AI reduces the time needed for analytics and allows detecting patterns. Let’s discuss the main areas where banks and Fintech companies use AI. If you would like to find out about other digital technologies used in the industry, please follow the link and read an article at

Risk Management (client scoring)

AI is used to assess the creditworthiness of potential money borrowers. It can analyze large amounts of data and foretell the credit risk with a high degree of precision. Banks and Fintech companies use machine-learning models to automatically score the applications for loans on the basis of the information about the applicant, his/ her credit history, sources of income, and other factors.

This is what the process looks like:

  • AI analyzes the applicant’s CV;
  • Compares the data with the bank’s requirements;
  • Analyzes the risk of non-return of the loan;
  • Suggest the decision.

Client support: chatbots and voice assistants

Banks and Fintech companies use virtual assistants on the basis of AI more and more often. This simplifies client support greatly. The assistants can answer clients’ questions, help perform various banking operations, and give information about transactions and the account balance. There is space for improvement because virtual assistants are unable to solve some tasks yet but the development process goes on and improvements are evident.

Sometimes, you could not tell a virtual assistant from a human operator: the former’s speech sounds natural and the manner of communication is quite human. A good chat box can replace several bank officers thus reducing the operational costs.

Counter fraud

AI is used in counter-fraud systems, for AML purposes, and other tasks that the Compliance Department has. AI finds patterns in the client’s behavior and signals about suspicious operations.

What makes a financial operation suspicious is its abnormality. AI is good at spotting an unusual characteristic of a transaction and it can draw humans’ attention to it.

It must be noted that AI is capable of telling the difference between an everyday situation when a child uses his/ her mother’s bank card without permission and an act of fraud when a professional criminal tries to carry out a banking operation.

Personalized marketing

IA helps identify the preferences and inclinations of a particular bank customer. Having this information, the system can put forward recommendations that are likely to be of interest to the customer. For example, when logging onto the bank’s webpage, the customer may see an ad that is relevant to his/ her interests.

Ideally, the recommendations have to be tailored not only to the customer but also to the means of communication that he/ she uses. In any case, when you see a pop-up ad on your computer or smartphone screen, you should be aware that the recommendation to show you this ad has been made by an AI system.

Robotic process automation

Banks and other financial institutions use AI to delegate routine tasks to robots. Robotic process automation allows processing applications for loans and checking the customers’ data by robots. This reduces the time of application processing and lowers the probability of mistakes. With the help of computer vision, for example, robots can extract clients’ data from printed documents, help them fill out application forms, and conduct client identification.

Digitized documentation is the reality in banking and Fintech. Digital documents can be accessed and verified in a fast manner.

Speech analytics

Banks are actively employing speech analytics tools based on AI. These tools allow systemizing and analyzing all the information recorded in call centers and bank offices. Human workers can analyze not more than 3% of oral information while AI can handle tons of it.

The system works non-stop and much faster than a human person does. This allows improving the quality of the services provided in call centers and increasing sales conversion.

Technologies used for speech processing are relatively new but AI mechanisms are already very good at talking with humans. When the client calls an AI-based cat bot, he or she can talk with it the same way he/ she would be talking to a human person. The chat bot understands the questions and gives clear answers.

Investments and portfolio management

AI can also be used for market analysis and portfolio management. A machine can analyze a huge amount of data and suggest optimal investment strategies.

Robots can also structure the information in an understandable way. When making investment recommendations, they turn out coherent texts and put forward clear arguments.

Data analysis and financial forecasts

AI is capable of analyzing large volumes of information and detecting hidden patterns. This allows them to forecast the results of certain future banking operations. Banks and Fintech companies use AI to determine the tendencies, to decide on the optimal prices of certain securities, and so on.

AI is also very helpful when it comes to analyzing transactions. With its help, bankers know what to expect from a particular client and they are put on alert if something unexpected happens.

Legal issues related to AI

Artificial intelligence has only started to penetrate various spheres of human lives. It is a new invention (if we are to speak about powerful AI, not about primitive AI) and it is unclear so far how AI should be regulated. It is a powerful business tool for banks in particular but some legal and moral issues arise when banks use AI in their operations.

In particular, giving access to people’s personal data to a machine raises serious questions. Can the machine use the data in an illegal way? Can it use the date to do harm to a natural person? What kind of morals should guide the machine when it uses people’s data and makes decisions?

Clearly, companies that use AI should be open about the reasons why they use it and the methods of its application. However, the technology is rapidly developing at the current moment and it’s hard to say what tasks it is going to be capable of solving. Depending on how powerful AI becomes, different regulatory measures may be required.