Digital Transformation and Ecosystem Evolution of Kazakhstan’s Banks: An Integrative Review and Conceptual Model

L. T. Kopbayeva

2026

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DOI 10.52821/2789-4401-2026-3-209-233
Data confidence 70 medium
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Abstract

Purpose of the research. The purpose of this article is to synthesize and systematize existing knowledge on the ecosystem competitiveness of Kazakhstani banks in the context of their transition to digital ecosystembased models, as well as to develop a conceptual model. Methodology. The study employs an integrative literature review method based on methodological guidelines, using the Scopus, Google Scholar, and Dimensions databases for the period 2010–2025. The conceptual framework is built around the linkage between ecosystem maturity (EM), orchestration capabilities (OC), data governance quality and use (DGQ), the strength of the data–network–activity (DNA) cycle, and ecosystem-based competitiveness (EBC), with regulatory openness (RO), legacy burden, and BigTech pressure acting as moderating factors. Originality / Value of the research. This study contributes to a holistic understanding of how the transition of Kazakhstani banks to digital ecosystem models affects their competitiveness. Its theoretical contribution lies in identifying research directions for future empirical and conceptual studies. The practical significance is reflected in the formulation of recommendations for prioritizing API partnerships, managing data quality, and standardizing interfaces. Findings . The integrative literature review reveals that, in addition to the validated mechanisms EM→OC/ DGQ→DNA→EBC, the academic community is divided into two competing theoretical schools: (i) innovationoriented and (ii) institutional–regulatory. The review also enables the development of an integrated model of pathways to ecosystem competitiveness for banks in Kazakhstan. Within this model, ecosystem competitiveness is shaped through the interaction of (1) technological and platform maturity, (2) orchestration and analytical capabilities, including data management and the development of network effects, and (3) institutional and market conditions, primarily the regulatory environment and competitive pressure from BigTech firms. Positive ecosystem effects emerge only when these components develop in a coordinated manner.