Proceedings of the International scientific and practical conference ―Science in the Era of Globalization‖ (May 22-24, 2026) / Publisher website: www.naukainfo.com. - Zurich, Switzerland, 2026. - 353 p.

125 including nominal value, currency, issue and maturity dates, yield, coupon type, payment frequency, market price, as well as temporal and contextual indicators. It is shown that the completeness and consistency of these parameters determine the feasibility of further modeling of financial offers and conducting analytical processing. A practical study of the data collection process from heterogeneous sources was conducted, including banking institutions (PrivatBank, Raiffeisen) and brokerage platforms (BTC Broker, ICU, Kinto, PrivatBank, PUMB, Raiffeisen, Univer). It was established that different sources provide non-uniform datasets, differ in data representation formats, and vary in accessibility levels (availability of APIs and web interfaces). It is separately noted that some financial institutions enable OVDP transactions but do not provide access to up-to-date structured data, which complicates the automation of data collection (UkrEximBank), while some institutions do not publish data publicly (Monobank, Sense Bank). The study substantiates the feasibility of a combined data collection approach integrating APIs, web scraping, and browser automation, followed by normalization, which enables the most efficient aggregation of data from diverse sources. As a result, a foundation has been formed for building a unified system for representing financial offerings in the OVDP market, which can be used for the further application of intelligent analytical methods, particularly models that take contextual factors into account. REFERENCES: 1. Azarov M., Lyashkevych V. Identification of consolidated data sources for financial proposal characteristics research. International Scientific Unity . 2025. P. 123–125. URL: https://doi.org/10.70286/isu-10.09.2025.008 (date of access: 20.05.2026). 2. Ionescu S.-A., Diaconita V., Radu A.-O. Engineering Sustainable Data Architectures for Modern Financial Institutions. Electronics . 2025. Vol. 14,