Development of Practical Recommendations for Cost Allocation System Transformation in the Insurance Company X

Keywords: overheads, automation, allocation, ABC, cost driver, insurance activities Abstract The insurance market in Russia is currently experiencing a significant transformation characterized by digitalization, market convergence, and escalating data volumes. This shift is primarily fueled by market consolidation and heightened customer expectations. To enhance their competitive edge, insurance companies are focusing on refining their resource allocation systems. However, it's apparent that Insurance Company X's allocation practices may not align with industry norms. This discrepancy could stem from various factors, including elevated labor costs, inadequate integration with databases, challenges in scaling data volumes, limited precision in departmental and product cost allocation, and insufficient information visualization. This study aims to propose recommendations for adapting and automating an indirect cost allocation model tailored to the unique characteristics of an insurance company. The analysis draws on primary data obtained through in-depth interviews with key personnel responsible for financial and operational management, supplemented by document reviews. Additionally, secondary sources such as consulting reports, industry publications, and academic literature were consulted. Special emphasis was placed on financial modeling to evaluate the economic viability of digitizing the allocation function, thereby assessing its potential impact. The findings reveal that automating the cost allocation function not only proves economically viable in this context but also promises to deliver added value to the company, particularly in terms of data quality improvement.