Social credit: a comprehensive literature review

Lean Yu · Xinxie Li · Ling Tang · Zongyi Zhang · Gang Kou

48 citations0/0 files storedFinancial Innovation

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Financial Distress and Bankruptcy Prediction Credit Risk and Financial Regulations Evaluation and Optimization Models

Abstract

To avoid credit fraud, social credit within an economic system has become an increasingly important criterion for the evaluation of economic agent activity and guaranteeing the development of a market economy with minimal supervision costs. This paper provides a comprehensive review of the social credit literature from the perspectives of theoretical foundation, scoring methods, and regulatory mechanisms. The study considers the credit of various economic agents within the social credit system such as countries (or governments), corporations, and individuals and their credit variations in online markets (i.e., network credit). A historical review of the theoretical (or model) development of economic agents is presented together with significant works and future research directions. Some interesting conclusions are summarized from the literature review. (1) Credit theory studies can be categorized into traditional and emerging schools both focusing on the economic explanation of social credit in conjunction with creation and evolution mechanisms. (2) The most popular credit scoring methods include expert systems, econometric models, artificial intelligence (AI) techniques, and their hybrid forms. Evaluation indexes should vary across different target agents. (3) The most pressing task for regulatory mechanisms that supervise social credit to avoid credit fraud is the establishment of shared credit databases with consistent data standards.

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1981Credit Rationing in Markets with Imperfect Information 1966Financial Ratios As Predictors of Failure 2002Does Distance Still Matter? The Information Revolution in Small Business Lending 2004Corporate Yield Spreads: Default Risk or Liquidity? New Evidence from the Credit Default Swap Market 1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions 2000Neural network credit scoring models 2003Credit rating analysis with support vector machines and neural networks: a market comparative study

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