ІНСТИТУЦІЙНИЙ РЕПОЗИТАРІЙ ДЕРЖАВНОГО ПОДАТКОВОГО УНІВЕРСИТЕТУ
Institutional Repository of the State Tax University (iRDPU)
ISSN 3083-6344
Вітаємо на цифровій платформі iRDPU, що забезпечує накопичення, систематизацію, обробку, зберігання та надання у відкритий доступ електронних версій інтелектуальних продуктів університетської спільноти.
Проєкт реалізовано на базі програмного забезпечення DSpace© та підтримується Науковою бібліотекою університету.
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Тип елементу:Документ, Цифрова трансформація бізнес моделей у фінансовому секторі економіки(Державний податковий університет, 2026)Дюк, Ростислав ІгоровичThe dissertation examines the theoretical foundations, methodological approaches, and practical aspects of the digital transformation of business models in the financial sector within the development of the platform economy. It is substantiated that digitalization has become a strategic factor in enhancing the competitiveness of financial institutions, driving the transition from traditional linear business models to platform-based ecosystems focused on multi-sided value creation. The essence of a financial institution’s business model under conditions of digital transformation is clarified, and the key principles of its adaptation and development are identified. The study reveals the role of platformization as a major direction of financial sector transformation and highlights the distinctive characteristics of digital platforms and ecosystems. Particular attention is paid to the impact of FinTech companies, artificial intelligence, big data analytics, blockchain technologies, cloud computing, and regulatory technologies (RegTech) on the formation of innovative business models. The current state and development trends of the digital transformation of Ukraine’s financial sector are analyzed. The main drivers, risks, and constraints of its development under wartime and economic challenges are identified. The research substantiates the importance of integrating cybersecurity into the architecture of digital business models as a key factor in ensuring resilience, trust, and sustainable development of financial institutions. Methodological approaches to selecting business model transformation strategies based on the level of digital maturity and the characteristics of ecosystem participation are proposed. The findings demonstrate that successful adaptation to the platform economy requires comprehensive organizational, technological, and managerial changes, which are essential for strengthening the competitiveness and long-term sustainability of financial institutions.Тип елементу:Документ, Створення модульної та інтерактивної системи моніторингу з адаптивним веб-інтерфейсом(Ірпінь, 2026)Упіров, Володимир ВолодимировичResearch on the processes of collecting, aggregating, and visualizing data from heterogeneous sources; analysis of existing solutions in the field of monitoring systems; justification of the choice of architectural solutions and development technologies; design of a modular platform architecture for collecting and processing metrics; development of an adaptive web interface for interactive real-time data visualization.Тип елементу:Документ, Розробка адаптивної системи для вивчення мов із використанням штучного інтелекту(Ірпінь, 2026)Мурга, Богдан ОлександровичComprehensive study of foreign language teaching methodologies was conducted and an innovative software product was implemented - an adaptive web application based on artificial intelligence. The Python programming language and relevant specialized libraries for the web environment were chosen for development. The result of this stage was the construction of a scalable architecture and the development of a minimum viable product (MVP) demonstrating the key capabilities of the AI module.Тип елементу:Документ, Система оцінювання кредитоспроможності позичальників методами Machine Learning(Ірпінь, 2026)Морозов, Ігор АртемовичThe thesis explores the application of machine learning methods for assessing borrowers’ creditworthiness. A comparative analysis of traditional credit scoring approaches and modern algorithms, including logistic regression, Random Forest, and LightGBM, is conducted. A practical credit scoring pipeline is developed with a focus on predictive accuracy, interpretability, and regulatory transparency. The results confirm the effectiveness of LightGBM for credit scoring tasks.Тип елементу:Документ, Розробка комп’ютеризованої системи замовлень в інтернет-магазині(Ірпінь, 2026)Міщук , Володимир ЮрійовичThe work includes the design of the web system architecture, the development of the database structure, the implementation of the software product, and its testing. The proposed system provides automation of the order processing workflow, information storage, and user interaction with the system
