Abstract

The rapid adoption of artificial intelligence (AI) in consumer markets has led to the need for extensive research into its impact on consumer behavior, particularly in how it exploits cognitive biases. This raises ethical questions and highlights the need to balance such influences with AI systems that help consumers, not manipulate them. The development and implementation of an intelligent financial management system, which not only automates financial processes, but also integrates AI-driven tools to support better financial decision-making, contributes to solving these problems. The work contains a description of the development of the architecture of an intelligent financial management system, which is aimed at solving problems related to financial illiteracy, the complexity of financial markets, and the impact of cognitive biases on financial decision-making. The system provides for the use of modern technologies of artificial intelligence and machine learning to automate financial processes and provide users with personalized recommendations. The development of a system based on microservice architecture requires the use of certain architectural patterns that ensure efficiency, reliability and scalability, so the work was based on a critical analysis of modern architectural paradigms, such as microservice architecture and Event-Driven Architecture. The implementation of AI supports ethical guidelines that prioritize transparency, fairness and consumer autonomy, i.e. ensure that the AI ​​system is free from bias, actions can be easily interpreted by users. The methodology of this research is based on an interdisciplinary approach that combines the analysis of architectural solutions, methods of machine learning and artificial intelligence with methods of ensuring the reliability and scalability of software systems.

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