Ovik Mkrtchyan, corporate consultant at Gor Investment Limited, is convinced that the use of artificial intelligence in fintech is qualitatively changing the industry. AI-based technologies allow financial market participants to make real technological breakthroughs in terms of security, personalisation of services, business modelling, and many other areas of activity.
Ovik Mkrtchyan believes that if the processes of banking activity are conditionally divided into three blocks, then the first block can be divided into management processes – namely, strategic management; management of banking products; and marketing, public relations, branch network development, distressed assets, risks, finance, quality, and personnel.
Diverse uses of AI in banking activities
AI has been actively used in the first block in processes and services such as customer scoring, business forecasting, customer segmentation, automatic robocalling, cash forecasting at ATMs and collection planning, and analysis of the location of offline points.
The second block is the main banking processes. It includes servicing retail and corporate clients, working with financial institutions, as well as activities within the stock, financial, and derivatives markets. The list of main AI solutions for these processes includes chatbots, voice assistants, as well as personalised electronic services, and personal financial assistants.
The third block of banking is the framework for all bank’s supporting activities – ACS, legal and IT, document management and accounting, security and internal control, as well as measures to combat proceeds from crime and the financing of terrorism.
In this last block, AI is also actively used in biometric identification technologies, document recognition, fraud monitoring, and detection of atypical financial activity.
Prime examples of AI in fintech
To understand why the use of AI is becoming a global trend in the digitalisation of the financial sector, one should consider a few typical uses of AI in fintech. For example, its speeds up many processes. AI-assisted customer scoring reduces application approval time from days to minutes. The cost of scoring is reduced, and its quality is growing, thus affecting the amount of delay.
Also, AI in voice assistants allows intelligent call routing within the call centre and it communicates with the client through a voice assistant inside applications. In practice today, it can independently receive up to 80% of calls in intelligent mode and then automatically processes 10% of responses without the need to contact an actual person. The result – service time for each customer decreased by an average of 40 seconds. If the voice assistant is implemented correctly, then in the voice queue a person waits much less, and if he does, then he is routed to the correct bank staff employee who can answer his request.
Another great example is smart chatbots. These are omnichannel means of communication in which customer voice recognition allows a chatbot to respond individually to that person. At the present time, 60% of customer requests are completely or partially dealt with automatically by bots and the average time to solve problems or respond to customer requests is reduced by an impressive four times.
Biometrics and anti-fraud are among the shining examples of the benefits of using AI in fintech. The first makes it possible to remotely open bank accounts and conduct financial transactions remotely, reducing the time for their implementation, while the accuracy of customer identification grows many times. Secondly, the use of AI to detect atypical activities can halt fraud attempts, thereby saving funds for both banks and customers.
AI-based cognitive technologies
Artificial intelligence is one of the key technologies that will seriously affect the development of the financial market in the near future. Many financial institutions are already using such technologies.
The quality of customer service is one of the most important components in the business of financial institutions. It is not surprising that this area was one of the first to be automated, both in terms of communications with customers and in terms of assessing their satisfaction.
Ovik Mkrtchyan believes that “customer satisfaction is a measurement that shows how a company’s product or service meets the client’s expectations. This is important because satisfied and loyal customers are the main driver of growth for the company.”
Ovik Mkrtchyan adds: “Financial companies need to constantly improve business processes, and update technologies in order to further improve the quality of customer service. Keeping up with the times means being successful.”