The Incentive and Supervision Mechanism of Banks on Third-Party B2B Platforms in Online Supply Chain Finance Using Big Data

摘要

The incentive and supervision design of cooperation between banks and B2B platforms was studied under the electronic warehouse receipt pledge financing model. Under the assumptions of B2B platform risk, neutrality, and risk aversion, a principal-agent model for cooperation was established between banks and B2B platforms. Its purpose was to expand and compare the models by adding supervision variables. It also helps to analyze the effects of risk aversion coefficients on effort level, fixed payment, incentive coefficients, and the impact of bank income. This paper has analyzed the banking system’s incentives and supervision mechanisms by performing numerical analysis on big data. We have used MATLAB for numerical analysis. The results show that banks’ expected benefits when cooperating with risk-neutral B2B platforms are always greater than the expected benefits obtained when cooperating with risk-averse B2B platforms. But when banks act, the increase in profits exceeds the cost of regulatory measures. Besides, when the bank takes supervisory measures, the profit will be greater than the profit without supervisory measures. Hence, the B2B platform’s ability to recover losses is positively correlated with the bank’s expected utility. The cost coefficient of the B2B platform is negatively correlated with the bank’s expected utility. The risk aversion degree does not affect the optimal effort level of the B2B platform, but it affects the optimal fixed payment and the optimal incentive coefficient.