【摘要】 目前,对微观信用评价理论和方法的研究基本上是针对条件、关系等因素在相对确定的状态下进行的,主要通过运用运筹学、回归分析、管理科学与数量经济学建立研究理论和方法,如博弈理论、数据包络理论以及区块链理论。在大数据环境中,微观信用的影响因素一般情况下是动态的,客观上动态的、非确定性、小概率、非正负相关的逻辑关系不明显,而随机性因素会对信用问题造成巨大影响。文章在国内外最新研究的基础上,指出在大数据环境下微观信用机制的研究方法和方向,并提出了研究路径。更多还原

【Abstract】 At present,the research on micro credit evaluation theory and method is basically based on the study of conditions and relationship factors in a relatively determined state,mainly through the application of operational research,regression analysis,management science and quantitative economics,such as game theory,data envelopment theory and blockchain theory,these theories and methods are also constantly developing and improving. In the big data environment,the influencing factors of micro credit are generally dynamic,objectively dynamic,non-deterministic,small probability,non-positive and negative,and logically insignificant. Random factors have a huge impact on credit issues. Based on the latest research at home and abroad as well as under the background of big data,this paper is trying to clarify the research methods and the directions of micro-credit mechanisms,and further propose the research approach.更多还原