UDC 005.334: 004.657
DOI: 10.36871/ek.up.p.r.2025.06.04.001
Authors
Sofia M. Syurkova,
Kazan National Research Technical University named after
A. N. Tupolev — KAI, Kazan, Russian Federation
Alyona V. Bogomolova,
Tomsk State University of Control Systems and Radioelectronics,
Tomsk, Russian Federation
Azat R. Shagiakhmitov,
Kazan Cooperative Institute — Branch of the Russian University
of Cooperation, Kazan, Russian Federation
Abstract
In the context of digital transformation of the corporate environment, big data technologies are gaining increasing importance, having a systemic impact on the methodology and practice of corporate finance management. The article reveals the essential characteristics of big data in the financial context and describes key areas of their applied use, including cash flow forecasting, liquidity management, risk assessment, and budget modeling. It examines the sources and structures of financially significant data, including corporate IT systems, open databases, transactional and unstructured data sets. The functionality of analytical and software solutions enabling the processing and interpretation of such data is presented, including business analytics platforms, machine learning technologies, and cloud services. The emphasis is placed on institutional and infrastructural constraints of digitalizing financial processes, as well as the potential effects of improving sustainability, accuracy, and proactivity in financial management through the use of big data.
Keywords
big data, corporate finance, business analytics, digitalization, machine learning, forecasting, budgeting, liquidity management, information systems, financial modeling
