Aim. IThe presented study aims to identify current trends and key directions for the introduction of quantum technologies into the management practices of Russian credit institutions to improve their performance in the medium term. Tasks. The authors comparatively analyze current trends in the application of quantum technologies in the banking business; forecast key trends in their development in the medium term in the context of the Russian banking sector. Methods. The authors use the methods of comparative and system analysis, scientific abstraction, and hypothesis. Results. Practical examples of the introduction of modern quantum technologies in the foreign and Russian banking business are provided. As a result, priority directions and areas of their application are identified with an emphasis on the domestic banking sector: credit scoring, assessment of the value and risk of investment, diversification of investment portfolios, financial forecasting, crisis prediction, fraud detection, protection of banking and customer databases from the quantum threat, and increasing the level of banking cybersecurity in general. Conclusions. Despite the novelty of quantum technologies in the banking business, the role they will play in banking in the near future is difficult to overestimate. Quantum computers can significantly improve the performance of banking IT systems by solving computational tasks that even super-powerful conventional computers are not able to tackle on their own. They significantly increase the efficiency of modeling complex systems and processes; accelerate the soultion of problems associated with resource optimization, logistics, finance, and trading; simplify work with big data using artificial intelligence (AI) and machine learning models in neural networks; help to combat cyber attacks and fraud in financial markets.
Aim. IThe presented study aims to identify current trends and key directions for the introduction of quantum technologies into the management practices of Russian credit institutions to improve their performance in the medium term. Tasks. The authors comparatively analyze current trends in the application of quantum technologies in the banking business; forecast key trends in their development in the medium term in the context of the Russian banking sector. Methods. The authors use the methods of comparative and system analysis, scientific abstraction, and hypothesis. Results. Practical examples of the introduction of modern quantum technologies in the foreign and Russian banking business are provided. As a result, priority directions and areas of their application are identified with an emphasis on the domestic banking sector: credit scoring, assessment of the value and risk of investment, diversification of investment portfolios, financial forecasting, crisis prediction, fraud detection, protection of banking and customer databases from the quantum threat, and increasing the level of banking cybersecurity in general. Conclusions. Despite the novelty of quantum technologies in the banking business, the role they will play in banking in the near future is difficult to overestimate. Quantum computers can significantly improve the performance of banking IT systems by solving computational tasks that even super-powerful conventional computers are not able to tackle on their own. They significantly increase the efficiency of modeling complex systems and processes; accelerate the soultion of problems associated with resource optimization, logistics, finance, and trading; simplify work with big data using artificial intelligence (AI) and machine learning models in neural networks; help to combat cyber attacks and fraud in financial markets.
In the modern world, the financial sector faces a wide range of extraordinary events, from market shocks and geopolitical tensions to pandemics and cyberattacks. These diverse challenges significantly impact banks. Recently, particular attention has been drawn to the influence of artificial intelligence (AI) and quantum computing (QC) technologies on the stability of the financial system. This article analyzes the potential areas of impact of quantum technologies on the financial sphere in general and the resilience of financial institutions in particular.It's determined that quantum technologies can simultaneously pose both threats and new opportunities. Specifically, the article analyzes the potential of quantum technologies to break existing cryptographic algorithms that protect the confidential data of financial institutions' clients. This threat is exacerbated by the possibility of "harvest now, decrypt later" attacks, where malicious actors intercept data today with the intention of decrypting it in the future. This presents challenges and threats for online/mobile banking, payment operations, and corporate communications. Among the positive impacts of quantum technologies on banking, the article highlights improved financial risk assessment, particularly enhanced accuracy in stress testing, portfolio management, and derivatives pricing, by solving problems inaccessible to classical computing. The potential of quantum machine learning for fraud detection is also noted. Attention is given to the financial sector's response to these challenges. Initiatives for developing quantum-resistant (post-quantum) cryptography are considered as the primary method for mitigating the risks associated with the proliferation of quantum computing, along with new cryptographic protocols and quantum key distribution as a new opportunity to enhance security. The article emphasizes the responsibility of central banks in forming quantum-readiness strategies, including investments in post-quantum cryptography, expertise development, and the adaptation of regulatory frameworks. The conclusion drawn is that although the immediate benefits of quantum technologies may be modest, their long-term transformative potential for the financial sector is immense.
Various ways in which quantum computing may transform the financial industry are also explored in this research, and this includes its potential to deal with the problems that we are currently faced with and the opportunities that it may bring. The research starts with a general survey of the existing situation in the area of quantum computing technology which contains lowering of costs and increase in effectiveness. It proposes how quantum computing can vastly change the current performance of banking regarding fraud detection, improvements in risk management measures, and better optimization of various financial process. Additionally, the report reviews the barriers and possible risks that exist in the banking industry implementing quantum computing techniques and, thus, offers crucial points for the successful mitigation of these risks. This study’s outcomes are expected to provide banks with helpful information on how they can exploit the capacities of quantum chips to reinforce their data security strategies and assert themselves against their competitors. The research results present the findings that are practical for the strategic application of quantum computing in the banking sector, identifying an opportunity for the transformative effects of the technology to start changing the expensive and inefficient banking processes and giving rise to a safe and efficient financial environment.
The development of quantum entanglement opens new opportunities for financial markets, facilitating faster data processing, optimizing strategies and improving risk management. Quantum algorithms, with their exponential computational power, are able to solve problems available for classical computers, which makes them promising for high-frequency trading, stress testing of banking systems and liquidity analysis. Introduction of quantum cryptography and optimization algorithms changes the approach to the security of financial operations and forecasting of asset dynamics. The article discusses the main directions of quantum computers use in finance, analyzes their consequences, potential threats and regulatory challenges. Special attention is paid to the impact of the quantum revolution on the financial sector of the economy and the possibility of its transition to new technologies.
Quantum Artificial Intelligence (Quantum AI) is a popular and new computational field that incorporates the use of quantum computing in enhancing Artificial Intelligence (AI). This chapter addresses the use of Quantum AI in three sectors, namely healthcare, finance, and cybersecurity, with a view that the deployment of AI integrated with Quantum computing shall take the respective industry to another level. Quantum AI enhances diagnosis and medical imaging, pattern recognition, and diagnostics, which increases the rate of accuracy or detection and diagnosis of diseases and illnesses. Moreover, Quantum AI optimizes portfolio management, risk evaluation, and prediction, and fraud detection in the financial industry, as well as enhances the computational rate in comparison to current rates. Quantum is used to enhance investment solutions and approaches to assess large amounts of big data as soon as possible, resulting in more potent risk management tools. Also, they improve the detection of fraud in financial transactions by providing a means of detecting the variation in such transactions, making security in online/mobile banking and other facets of electronic payment firmer. On the same level, they defend computer networks and systems from cyber-attacks through massive and complicated structures of analyzing large data sets in an incredibly short period. Technology has certain drawbacks, which include issues in quantum computer hardware, errors that could be present in quantum structures, and moral issues relating to the safety of data and information. A solution to these challenges could only be good if Quantum AI becomes widely implemented across the numerous domains of industry today. This Chapter gives an elaborate overview of the relevance of Quantum AI in healthcare, finance, and cybersecurity, which defines the trend of intelligent and secure computing systems.
The rise of quantum computing presents a profound shift in the cybersecurity landscape, particularly for the banking and finance sectors, where the protection of sensitive data is paramount. Traditional encryption methods are increasingly at risk of being compromised by the computational power of quantum machines, demanding the adoption of quantum-resistant technologies. This discussion delves into quantum key distribution (QKD) and post-quantum cryptographic algorithms, exploring their potential to secure financial transactions, protect customer information, and reinforce the integrity of banking networks. The application of these technologies offers new avenues for safeguarding data against quantum attacks while also addressing the challenges associated with integrating quantum security into existing infrastructures. The exploration also highlights the risks posed by quantum computers to current cryptographic systems and provides guidance on how financial institutions can transition to quantum-secure frameworks. By embracing these innovations, the banking and finance sectors can build resilience against future cyber threats in an era of quantum computing.
Due to the rapid development of artificial intelligence (AI) technologies, marketing professionals are faced with a changing landscape that requires a comprehensive understanding of the potential and challenges of AI applications. Quantum computing processes are the basis for the future development of predictive analytics, as their ability to simultaneously provide many variants of events with different variations of their occurrence allows achieving reliability of up to 99.75%, even in conditions of irrationality. The relevance of the research is related to the state priority for the development of quantum technologies, as well as technological advances, in particular, ease of use and accuracy of the data obtained. The research is aimed at determining the combination of AI technologies with the use of quantum computing processes that is most suitable for the tasks of marketing analytics in order to increase the accuracy of forecasting consumer behavior and market mechanisms in the long term. The methodological basis of the research was scientific work in the field of marketing strategies, artificial intelligence, as well as descriptions of the basics of quantum computers, practical work of leading centers for the implementation of quantum computing in business processes. The theoretical basis is bibliometric analysis, theory of quantitative methods, theory of innovation. For the purposes of the research, literature was analyzed and various AI software products were systematized, a list of cases was provided and practical results in the field of quantum computing application in predictive analytics in the field of marketing were compared. Their impact on such marketing components as market analysis and forecasting, audience sentiment analysis, and offer personalization is assessed. The information base consisted of a study of 160 articles written in the field of predictive analytics based on AI for marketing purposes, as well as an assessment of 26 cases of the use of quantum computing in business processes both in Russia and abroad. The key focus of the research is a critical assessment of the benefits of implementing artificial intelligence technologies in conjunction with quantum computing processes in shaping marketing strategies, including long—term forecasts of consumer behavior and changes in market mechanisms. The result of the research is a framework for the introduction of artificial intelligence technologies in conjunction with quantum computing processes in the formation of marketing strategies.