UX Approaches to the Integration of Artificial Intelligence into User Scenarios of Digital Financial Platforms

The article examines the integration of artificial intelligence tools into user scenarios of digital financial platforms from the perspective of user experience approaches. It investigates how the choice of forms of visualizing predictive data, the degree of autonomy of intelligent agents and the mechanisms for explaining results affect the perception of services, the level of trust and users’ willingness to delegate routine operations to algorithms. It analyzes the balance between automation and the preservation of user control, as well as the role of adaptive personalization based on machine learning in shaping sustainable models of interaction with financial products.

digital financial platforms, user interface, artificial intelligence, machine learning

1. Elhamdadi, H., Stefkovics, A., Beyer, J., Moerth, E., Pfister, H., Bearfield, C.X., Nobre, C. (2023). Vistrust: a multidimensional framework and empirical study of trust in data visualizations. IEEE Transactions on Visualization and Computer Graphics. Vol. 30. № 1. Р. 348-358. [Google Scholar] [Crossref]

2. Sarna, S.A., Mohammed, A.A., Miah, M.R. (2025). AI-Powered Financial Analytics and Visualization Tools: The Evolving Landscape of Strategic Finance. Journal of Economics, Finance and Accounting Studies. 2025. Vol. 7. № 5. P. 60-82. [Google Scholar] [Crossref]

3. Naidenova, M. (2025). Automated procurement system in construction based on ERP (1C), EDI, and BIM: architecture, integration principles, and managerial impact. International Journal of Civil Engineering and Architecture Engineering. Vol. 6(2B). P. 85-90. [Google Scholar] [Crossref]

4. Joshi, S. (2025). A Comprehensive Review of Gen AI Agents: Applications and Frameworks in Finance, Investments and Risk Domains. International Journal of Innovative Science and Research Technology. Р. 1339-1355. [Google Scholar] [Crossref]

5. Bordusenko, D. (2025). Integration of machine learning into management accounting systems: forecasting operating costs and profitability in manufacturing. Cold Science. № 22. P. 70-81. [Google Scholar] [Crossref]

6. Rodriguez-Fernandez, F. (2025). Artificial intelligence and economic psychology: toward a theory of algorithmic cognitive influence. AI SOCIETY. Р. 1-12. [Google Scholar] [Crossref]

7. Habil, S., El-Deeb, S., El-Bassiouny, N. (2023). AI-based recommendation systems: the ultimate solution for market prediction and targeting. The Palgrave handbook of interactive marketing. Cham: Springer International Publishing. Р. 683-704. [Google Scholar] [Crossref]

8. Dulloo, R., Struweg, I. (2025). The Rise of Experience Economy and Marketing 5.0: Navigating the New Paradigm of Value Creation. Leveraging AI-Powered Marketing in the Experience-Driven Economy. IGI Global Scientific Publishing. Р. 1-38. [Google Scholar] [Crossref]

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