e-ISSN 2518-1181
DOI 10.33146/2518-1181
Online Media ID R40-06293
← Back Published: 30.10.2025

Big Data and Artificial Intelligence in Accounting and Information Systems of Insurance Business Stakeholders

Authors

Maryna Demianchuk Odesa I.I. Mechnikov National University, Odesa, Ukraine ORCID 0000-0002-3907-3464
Oksana Savastieieva Odesa I.I. Mechnikov National University, Odesa, Ukraine ORCID 0000-0002-7356-8890
Oleksandr Kuruch Odesa I.I. Mechnikov National University, Odesa, Ukraine ORCID 0009-0003-7165-5805

DOI:

https://doi.org/10.33146/2518-1181-2025-3(109)-5-13

Abstract

Today, the volume of data generated by insurance market participants is growing exponentially, and traditional Accounting Information Systems (AIS) cannot always provide analytical support in real time. Presenting a systematic analysis of the structure and functioning of information and analytical ecosystems of insurance business stakeholders (IBS) that integrate AIS, Big Data, and AI technologies, the article provides answers to three questions: Which key IBS generate and consume information flows within modern AIS, and how can these flows be classified by type and frequency of occurrence? How does integrating Big Data and AI technologies alter the structure, processing, and utilisation of information flows for financial accounting and managerial control of IBS? What synergistic effects does the combination of Big Data, AI, and AIS in IBS provide regarding financial data accuracy, process transparency, and the speed of managerial decision-making? The methodological basis of the study is a set of complementary methods, in particular, systematic analysis, a classification-typological approach, and structural-functional modelling. These methods allowed the identification of the main and auxiliary IBS, the classification of information flows according to their structure, frequency of receipt, and data sensitivity, and the construction of generalised schemes illustrating their interaction with AIS, Big Data, and AI. The researchers identified the main and auxiliary entities of the insurance business and classified information flows by structuring, frequency of receipt, and data sensitivity. The study results show that integrating Big Data and AI into AIS ensures accounting automation, accelerates management decision-making, and improves the accuracy of financial data and the transparency of management processes. The article develops models of multilevel interactions between technological components and IBS, demonstrating the synergistic effects of integrating advanced technologies. Insurance business stakeholders can use the results of this study to optimise the digital transformation of their AIS, enhance risk management efficiency, and support the development of personalised insurance products.

Keywords

Big Data, artificial intelligence, accounting and information systems, insurance business entities, information and analytical ecosystems, management decisions, digital transformation
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