The financial sector is currently one of the innovation leaders, as it’s precisely innovations that allow banks to remain competitive in a market where everyone offers nearly identical products and services. The demand for digital solutions in the financial sector continues to grow: according to Strategy Partners’ forecast, the Russian fintech market will grow by an average of 13.5% per year in the coming years. Machine learning algorithms, forecasting systems, and real-time data analysis tools are no longer a thing of the future but a reality that is changing the approach to risk management, fraud prevention, and the automation of financial processes. Let’s consider the trends that stand out in the Russian market and the technologies that banks are already using today.
Trends in the Russian banking sector
The need for any systemically important bank to innovate in the field of information technology is the ability to keep pace with the digital transformation of the entire industry, to change along with the country’s financial system, and, consequently, to become more attractive to customers.
Unquestionably, there is a high demand among players for data management technologies. Well-structured data management processes can significantly improve the quality of customer offers and the speed of decision-making. The consequence of well-structured data management is an inevitable increase in customer loyalty and retention, increased sales of banking products, and, consequently, a more confident position in the highly competitive banking services market.
Today, in the context of building the country’s technological sovereignty, the banking sector, as one of the key sectors of the economy, is choosing Russian solutions for working with data. The departure of key DBMS suppliers has become a serious test for the entire Russian fintech industry, but Russian developers have already quite successfully taken over the vacated niches and offer their own technologically advanced, mature products. When choosing software, banks are looking not just for a replacement for the products of departed vendors, but for options that offer modern approaches and have the potential for further development.
Undoubtedly, in the foreseeable future, technologies in the fields of artificial intelligence (AI) and rapid data processing for real-time decision-making will actively develop. AI in the banking sector is already proving to be a fairly mature technology: if a few years ago it was used primarily for credit scoring, risk assessment, and automation of customer service, today its application has expanded to creating a personalized customer experience and analyzing the emotional state of customers during service in retail branches. AI helps to cope with operational tasks faster, automate some internal processes, which significantly speeds up the speed of service and improves service. AI algorithms are also widely used in processing large volumes of data, communicating with customers using voice assistants and chatbots, and in combating fraud.
Banks analyze data here and now to personalize offers and retain customers. To do this, organizations are actively seeking ways to enrich customer data, use advanced analytics systems and machine learning technologies that allow them to process huge amounts of data in real time. They are able to analyze customer transactions, their interest in bank products and services, predict their behavior, and dynamically adjust the offer to a specific person. For example, if a bank understands that a customer is in a shopping center and may need money, it sends an SMS with an offer to issue a credit card. If the bank notices that the customer is abroad and their credit card limit is close to being exhausted, it promptly offers to expand the limit.
Stakeholder opinions
Many Russian banks focus on data as a basic asset around which all core processes are built. According to Nikolai Shevtsov, CDO of OTP Bank, an important goal for them today is to build data governance processes in order to form a reliable foundation for data management at the level of the entire company. The bank’s strategic directions today also include building a data management culture, creating a unified data and metadata storage architecture, implementing centralized data quality management processes, as well as developing analytical platforms, machine learning, and artificial intelligence systems. At OTP Bank, AI algorithms are actively used in customer services, personalized products, marketing campaigns, and communication with customers through chatbots and voice assistants.
According to Alexander Saburov, Director of the Big Data Department at Rosselkhozbank, the bank is actively investing in the development of innovative technologies. The department tests new solutions and tools designed to enable real-time analytics, both for enhancing customer experience through better client profiling and for optimizing the bank’s internal processes. Additionally, Rosselkhozbank is focused on exploring new cluster technologies for data management, which facilitates handling larger volumes of information and expanding the range of tools available to all data specialists within the organization.
VTB has established an Innovation Management System to foster the development of modern technologies. The system comprises the VTB Accelerator, the Venture Studio, and the VTB Technology Lab. According to the VTB Press Service, this framework allows to swiftly identify promising projects and advanced solutions in the open market, test them, and make informed decisions regarding their further implementation based on the results.
The bank also actively pursues its own technology initiatives, with a particular focus on artificial intelligence (AI) to enhance customer service quality and ensure robust protection of client funds. AI is already being used to evaluate risks during loan issuance and to assess the likelihood of clients falling victim to fraud. Additionally, VTB plans to introduce AI-powered digital advisors for every client and employee within the next two years. According to the bank’s press service, these innovations not only boost customer satisfaction but also optimize internal processes and drive revenue growth.
What to expect in 2025
In today’s competitive banking landscape, simply meeting each client’s expectations is no longer sufficient for success. To thrive, a modern bank must anticipate users’ needs. Currently, the transformation of banking services and products is guided by the principles of personalized approaches and the creation of flexible, tailored offerings for each client.
To meet these goals, banks are increasingly integrating artificial intelligence into their daily operations to accurately predict customer interests and create personalized offers. This level of personalization has a proven positive impact on conversion rates.
Real-time analytics is also becoming more prevalent, with near-instant data processing technologies expected to become the industry standard. Real-time decision-making will enhance service quality, enable the immediate detection of fraudulent transactions, and deliver more precise recommendations and tailored offers to customers.
In the year ahead, banks will focus on enhancing data quality and implementing more rigorous data governance practices. They will intensify oversight of data processing, classification, and storage to ensure greater reliability and compliance with regulatory standards. Ethical considerations in the use of clients’ personal data will also receive heightened attention. Banks will prioritize transparency in data collection, processing, and storage practices, fostering stronger trust with their clients. These efforts will not only strengthen customer relationships but also ensure better adherence to stringent regulations governing the handling of personal data.
Modern technological solutions go beyond automating routine tasks; they enhance internal processes in banks while making financial services more accessible, convenient, personalized, and secure for clients. Russian banks are actively adopting innovations, aiming not only to boost efficiency but also to deliver high-quality service and a diverse range of offerings for clients across all categories.
By Yulia Ilyina, Director of the Financial Sector and International Business Department at Arenadata Group