Research On Debt Risk Pre-warning Of Enterprise A Based On The Construction Of Intelligent Debt Management System

Since 2015,in order to adapt to and lead the new situation,state-owned enterprises have fully implemented the "three reduction,one supplement and one drop",but local state-owned enterprises have continued to operate high credit risk events,the reason why is that the immature development of the regulatory mechanism,short of market advantages and the lack of state’s restrictions on it,then its debt risk has greatly increased.The highway is an important infrastructure of the national economy.Local state-owned enterprises have dominant role in almost all of highway investment construction,operation and management.However,this infrastructure needs too much money to support and long time to recover.From 2014 to 2020,the gap between the receiving and expenditure has been expanding.What’s more,its debt management information is compromised and timeliness,so traditional management methods cannot support it.With the development of information technology,some scholars have proposed the concept of "intelligent management system",that is,based on digitalization and other technologies,through standardized processes and full information sharing to help managers carry out scientific decision on debts.The risk pre-warning analysis method has conducted more research since 1966 and has a relatively complete theoretical basis,but the research more focus on government debt risk pre-warning system.This article has selected the intelligent debt management system of large state-owned Enterprise A in Yunnan Province as an example.Since it started official launch of the intelligent debt management system construction project in January2021,the system basically meets the debt management requirements,but it still can be improved combined with the research related to the construction of the debt warning system and pre-warning analysis method.To improve it,firstly this article analyzes the current status of Enterprise A debt risk,then it combines the current status and demand analysis of the debt risk management of this company and informs the process of the Enterprise A,finally applying the new model in Enterprise A and put forward debt management suggestions.Research on debt Risk Pre-warning of Enterprise A based on the construction of intelligent debt management system,the following conclusions are drawn:(1)Debt data acquisition,debt-related application process and debt early warning are optimized after the improved intelligent debt management system of Enterprise A.(2)Although the expressway industry enterprises,represented by Enterprise A,have no debt crisis in the short term due to the advantage of policies,their income cannot maintain the repayment of the high interest and principal of long-term debt,which makes them actually have greater debt risk than seems.On the basis of strengthening their own profitability,they also should control the debt risk through the intelligent debt management system.In response to these problems,this paper puts forward the following suggestions:(1)The government and relevant departments should strengthen the policy guidance,the highway industry enterprises themselves should do a good job in debt analysis and fund use plan,adjust the debt structure,take the initiative to contact banks and relevant departments to obtain credit and subsidy funds,attach importance to the information management of debt,establish and continue to update the early warning system,pay attention to policy changes,and establish the repayment reserve system.(2)The construction of intelligent management system should closely focus on national policies,industry characteristics and its own management needs,use data processing and analysis methods as guidance,strengthen the ability of data sharing and utilization,build a standardized,automated and informationized command management system,and pay attention to information security issues in the construction of intelligent management system.It is expected that this study can provide reference for other enterprises that are implementing the construction of intelligent debt management system.