We use a few cookies

Essential cookies keep the library working. With your permission, we'd also like to use analytics to see what's useful and improve the experience. Read our Privacy Policy or Cookie Policy.

Skip to main content
Home/e-Resources/Computer Science & Information Technology/Recommendation system for financial decision-making using Artificial intelligence
PeriodicalsComputer Science & Information Technology

Recommendation system for financial decision-making using Artificial intelligence

Checking your access to this record.

Abstract & Overview

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 financi al 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.

Cite this record

Kostiantyn A. Shuryhin, Т. М. Сабирова (2024). Recommendation system for financial decision-making using Artificial intelligence. Applied Aspects of Information Technology, 7(4), 348–358. https://doi.org/10.15276/aait.07.2024.24

Copy in another style

Shuryhin, K. A., & Сабирова, Т. М. (2024). Recommendation system for financial decision-making using Artificial intelligence. Applied Aspects of Information Technology, 7(4), 348–358. https://doi.org/10.15276/aait.07.2024.24
Author names are used as deposited, so check their order before you submit.

Metadata is harvested from open-access indexes and can be incomplete. Check a citation against the published version before relying on it — see our open access & attribution policy.