Unraveling the role of data sharing in open finance diffusion: an evolutionary game approach on complex networks - Dongqing Chen; Chaoqun Ma; Liwei Zhang; Lijie Li (Future Business Journal)
Abstract Data sharing has become a transformative force in the global financial ecosystem, driving the evolution from open banking to open finance. In this study, we develop a diffusion model using evolutionary game theory on complex networks to explore how data sharing influences lenders’ micro-level decision-making and promotes the macro-level diffusion of open finance. Combined with empirical observations from China’s open banking initiatives, our findings reveal that the diffusion rate of open finance remains suboptimal, with lenders adopting open finance not yet realizing significant profit advantages over traditional practices. Furthermore, sensitivity tests performed through univariate analysis show that increasing either the proportion of data sharing active borrowers or their degree of data sharing plays a critical role in accelerating open finance diffusion, following distinct nonlinear exponential and linear growth trends, respectively. Notably, data sharing active borrowers dominating the market benefit from the inclusivity of open finance, where lenders’ profits are enhanced with a higher degree of data sharing. Thus, a mutually beneficial outcome arises when both the proportion of data sharing active borrowers and their degree of data sharing are maximized. We further perform several analyses to highlight the robustness of our main results, including analyzing the effects of lender strategy updates and government subsidies and extending a hybrid model that combines small-world and scale-free networks. This article suggests that policymakers should mandate secure data sharing ecosystems through privacy-centric regulation while implementing incentives like early adopter subsidies to accelerate open finance diffusion. Financial institutions must concurrently develop robust data guardianship systems using advanced encryption and federated learning technologies, transforming shared data into personalized credit innovations. These findings offer global implications, demonstrating how strategic data sharing frameworks can drive financial innovation, financial inclusion, and consumer protection across diverse regulatory regimes.