Recommendation system for financial decision-making using Artificial intelligence

Abstract

The rapid expansion of artificial intelligence (AI) in consumer markets presents challenges, particularly in how cognitive biases
influence financial decision-making. These biases can lead to irrational spending, raising ethical concerns about AI’s role in such
applications. This research explores how AI can enhance decision-making effectiveness and support consumers in making more
rational financial choices. The focus is on developing an intelligent financial management system that applies modern AI algorithms
to analyze financial behavior, detect anomalies, and offer personalized recommendations. The article considers a system for
generating personalized financial recommendations based on large language models, which uses transaction history, predicted costs,
and anomaly information to generate individual advice. Techniques include using Isolation Forest for identifying atypical financial
actions and a combination of ARIMA and LSTM models for budget forecasting. The research also considers integrating these models
with large language models (LLMs) to generate personalized recommendations. The methodological part of the work includes an
analysis of existing models and their areas of application, defining data types and structures for processing, developing a system that
integrates the available models, and testing it. The process of generating recommendations is described, which includes the stages of
processing input data, forming context, generating recommendations and evaluating them taking into account user characteristics,
such as risk level, financial goals and preferences. The generated recommendations are aimed at optimizing the user's financial
behavior and can be adapted to different income levels. Special attention is paid to the ethical aspects of the system, which include
ensuring confidentiality, fairness and transparency, as well as the importance of supporting user autonomy in making financial
decisions. The system promotes responsible financial behavior by helping to avoid impulsive spending and increasing financial
awareness without manipulation or imposing specific decisions.