The fintech industry is undergoing significant changes every day, largely due to the introduction of artificial intelligence (AI). This advanced technology, according to expert Sergey Kondratenko, not only opened up new horizons, but also optimised processes, strengthened the level of security and improved the quality of customer service. But in addition to its many benefits, AI also introduces its own risks that are important to users. So, the question arises: how exactly is AI changing the fintech industry today, what advantages does it bring and what innovations await us ahead?
Sergey Kondratenko is a recognised specialist in a wide range of e-commerce services with experience for many years. Now, Sergey is the owner and leader of a group of companies engaged not only in different segments of e-commerce, but also successfully operating in different jurisdictions, represented on all continents of the world. The main goal is to drive new traffic, create and deliver an online experience that will endear users to the brand, and turn visitors into customers while maximising overall profitability of the online business.
According to surveys, currently about 2/3 of fintech companies use AI technologies in their activities to varying degrees. Their influence continues to grow. Last year, the global market for AI solutions in the fintech sector was assessed approximately $9 billion. According to experts, this amount will triple in the coming years and exceed $31 billion by 2027. This suggests that the fintech industry is on the path to dramatic change, and AI will be one of the main drivers of this revolution.
Artificial intelligence in forecasting and minimising financial risks for companies and users
In today’s dynamic financial landscape, effective risk management is of utmost importance. With the rapid development of technology, AI has become a powerful tool in the practice of financial risk management, emphasises Sergey Kondratenko. For example, machine learning algorithms can analyse huge amounts of historical data to accurately assess credit risk. AI-powered fraud detection systems can identify patterns and anomalies in real time, minimizing financial losses. When analysing market risks, algorithms based on AI are used. They process large amounts of data and generate predictive insights. Operational risk management and regulatory compliance can also be improved through the automation and efficiency of AI-powered systems.
The integration of artificial intelligence into financial risk management provides many advantages and opportunities, says Sergey Kondratenko:
– Firstly, AI can improve the accuracy of risk detection and forecasting by analysing complex data sets and identifying patterns that humans may not notice. Secondly, the level of automation and efficiency increases as AI algorithms can perform repetitive tasks. This reduces the number of errors that could be made during manual work and frees up resources for more strategic activities.
Additionally, AI allows financial institutions to process vast amounts of data in real time. This ensures proactive risk management and timely decision making. AI is also capable of identifying previously undetected patterns and anomalies, providing valuable insights for risk mitigation.
Sergey Kondratenko: Main challenges of AI in financial risk management
Despite the enormous potential of AI, there are challenges and issues to be addressed regarding its application in financial risk management.
- The quality and availability of data requires its timely placement and updating, which does not always work due to possible failures in the system. These are also the most important factors, since accurate data is necessary for effective training of AI models.
- Another challenge, according to Sergey Kondratenko, is the interpretability of models, since AI algorithms can sometimes produce complex and opaque results, which requires additional effort to achieve compliance.
- Ethical considerations related to privacy and data security are also important when using AI in risk management.
Sergey Kondratenko is convinced that AI opens up vast opportunities for financial organisations to improve risk management practices. By leveraging technologies such as machine learning, natural language processing and predictive analytics, finance professionals and risk managers can benefit from better risk identification, automation and decision-making, he said. However, to fully exploit the potential of AI in financial risk management, it is critical to address challenges related to data quality, model interpretability, and ethical considerations.
Artificial Intelligence and Automated Solutions for Portfolio Management
In an era where retail goods can be ordered and delivered the same day using the Internet, it is not surprising that people want their financial transactions to also happen in real time and decisions to be made within minutes. In this regard, there is an increase in online and mobile banking, market lending, new digital payment options and automated solutions to speed up processes, reports Sergey Kondratenko. The specialist says that one of the areas of using AI is underwriting automation. It allows you to speed up credit checks of loan applicants and make approval decisions faster.
According to Sergey Kondratenko, those who want to become more familiar with the automation of fintech services using AI technologies should learn about the capabilities of virtual assistants.
Virtual Customer Assistants (VCA)
Increased capabilities in responding to customer requests using AI have led to the emergence of virtual assistants. For example, in 2018, Bank of America introduced its version of such an assistant called Erica. In three years, from 2019 to 2021, its user base increased from 6.3 million to 19.5 million, and the total number of interactions on the app nearly quadrupled, from 27.8 million to 105.6 million.
– However, Erica is only one of many trends identified by the analyst company Gartner. According to the company’s forecasts, in 70% of customer interactions, completely new technologies will be used, such as machine learning (ML) applications, chatbots and mobile messages, says Sergey Kondratenko.
Reality may show an even higher percentage of use of virtual assistants in fintech, the expert suggests, as digital solutions are now rapidly becoming popular among clients. This is good news for banks and fintech companies, which have been trying for years to get customers to use automated services to cut costs.
Robots and automation
Financial companies and institutions are also already using robotic process automation (RPA). Among them is BNY Mellon, which has begun implementing robots as a way to harness the power of AI to reduce costs and improve operational efficiency.
The cost savings were significant. In 2017, Reuters reported that the bank estimated annual savings of $300,000 as a result of moving from manual processes performed by people to automation provided through bots.
Sergey Kondratenko explains that robo-advisors have evolved from online surveys to specialised fund and portfolio management, algorithmic rebalancing and suggestions. He predicts that more automated technologies will soon appear to help investors:
– These AI algorithms are able to take into account a range of individual factors, including the client’s financial goals, budget and risk tolerance. As they mature, these “advisors” will be able to predict market trends and even determine when and how portfolios should be rebalanced.
Machine learning applications offer security solutions that eliminate many of the tedious tasks of conducting manual checks. The combination of predictive analytics and real-time data integration allows you to detect financial fraud threats as they arise.
Such intelligent automation in fintech is certainly a progressive step that is gradually displacing manual control and the human factor from this industry.
– There are many benefits to using AI in the fintech sector. One of the main ones is higher efficiency and productivity, which can be achieved through automation or optimisation of various processes, says Sergey Kondratenko.
These include things like providing credit, managing finances, detecting illegal activities or assessing risks. AI also helps reduce the risk of errors, increases the speed of decision-making and improves the customer experience. Medium and large fintech organisations are integrating AI into their operations to improve service standards, adapt to dynamic customer demands, and compete more effectively in the financial industry.