Analysis of Social Risks of Intelligent Video Monitoring in Kazakhstan

Andrey Samoilov, Zh. T. Smagul, A. N. Mamyrbayev

Qainar Journal of Social Science, 2026

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DOI 10.58732/2958-7212-2026-2-65-82
Data confidence 70 medium
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Abstract

The growth of digitalization and the development of the smart city concept contribute to the active implementation of public-private partnership (hereinafter – PPP) projects using artificial intelligence technologies in the field of urban infrastructure and road safety. The purpose of this study is to assess the social risks of the Sergek intelligent video monitoring project in Kazakhstan, implemented within the framework of the smart city concept, using methods of system dynamics and sensitivity analysis of the discounted cash flow indicator. The research methodology is based on the study of project data, followed by the construction of a project model using system dynamics (hereinafter – SD), which allows us to demonstrate various scenarios of the impact of risk factors. The study uses data from open sources, including information from the PPP Portal of the Republic of Kazakhstan, data from the Akimat of Almaty and the National Bank of the Republic of Kazakhstan. The simulation results showed that the highest discounted cash flow (hereinafter – DCF) is observed in the baseline scenario without taking into account risks and reaches 7,668,340,000 tenge in 2024, decreasing to 6,781,390,000 tenge in 2025. The greatest negative impact on the financial stability of the project is the social risk associated with a shortage of revenue from fines, at which the DCF value is reduced to KZT 6,287,440,000. The results obtained indicate that social risk is the most significant factor in the financial stability of an intelligent video monitoring project.