Research On Enterprise Receivables Control System Based On Grounded Theory

Enterprise accounts receivable is an important part of the company's current assets,and it is one of the important indicators affecting the company's capital turnover and corporate profits.There is a potential risk of customer payment default before any sales revenue is recovered before the payment is fully recovered.This kind of risk is called"credit risk",and the management of "credit risk" is "credit management".The main customers of the research object H in this paper are concentrated in the ultra-long-term overdue payment industries of construction,energy,automobile and rail transit.Therefore,H enterprises are under great pressure on the control of accounts receivable.At present,the research on receivables control focuses on financial institutions such as financial institutions or debt management companies,forming a relatively mature system of credit evaluation and credit management.The traditional 5C is more common in credit evaluation and forecasting.The evaluation model,the feature analysis model,the Z-SCORE model,and the big data risk control model based on big data analysis and deep mining technology generated by the development of Internet technology in recent years.Focusing on corporate credit management is limited by the characteristics of customer groups and industry characteristics.There is a big difference between corporate credit management and financial industry credit management.The main reason is the difference in market position and data environment.Bank-based financial institutions have a strong market position in credit management,and can require credit information to provide financial statements,audit reports,property certificates,credit records,and other data information for credit evaluation.The fundamental reason for the credit behavior of enterprises in the supply chain is that the market position is weak,and enterprises with strong market positions,such as industry leaders and aviation industry,will not give credit to the downstream.The weak market position requires credit behavior to help the business development.Naturally,the transaction object cannot be required to provide very detailed data.The enterprise must find some information about the customer's own credit situation in very limited and messy data.This is enterprise credit management.Environmental characteristics.Based on the customer type and business characteristics of the business-oriented enterprises,this paper analyzes the current situation of H-type accounts receivable control system and the characteristics of customer groups,and uses the research method of grounded theory to screen out the risk evaluation of accounts receivable of H enterprises.The key risk factors,with these risk factors as the main label,combined with the existing customer rating credit model of H enterprises,integrate the big data information of enterprise operations into the risk control process of H enterprises,and construct the risk control big data of accounts receivable.The logical model diagram of the model.This paper provides an enterprise credit risk assessment process.When the company conducts credit risk assessment,it can obtain the key label module(risk variable)of the target company's solvency and debt repayment ability,and preprocess these label data.Then through the default model,calculate the default risk of accounts receivable,and finally output the credit analysis conclusion to support the credit decision.