Evolutionary game analysis of FinTech transformation: A social co-governance pattern of peer-to-peer lending market in China - Wang, Qi; Liu, Xin; Zhang, Chenghu (Frontiers in Psychology, 2022)
To facilitate the transformation of the P2P lending market, this paper proposes a social co-governance pattern for protecting investors’ interests under the background of the benign exist of P2P lending platforms in China. We build a tripartite evolutionary game model to capture the behavior strategies of P2P lending platforms, investors, and financial regulators. The major effects which affect the formation of the social co-governance pattern are determined. The results demonstrate that there are four evolutionary stable strategies for the game model, among which the positive disposal of P2P lending platforms, the participation of the investors, and the co-governance policy of financial regulators is the optimal strategy. The initial proportion of P2P lending platforms, investors and financial regulators would significantly affect the convergence speed of the evolutionary stable strategy. A threshold effect exists, which may affect the formation of the social co-governance pattern. By designing reasonable incentive, penalty, and reputation mechanisms, the social co-governance pattern will effectively protect interests of the investors. This paper provides in-depth implications for protecting investors’ interests regarding the transformation of P2P lending market, and sheds lights for enhancing the sustainable development of the FinTech industry.