Research On Financial Risk Early Warning Of Real Estate Companies Based On Machine Learning

In 2021,leaders of the National Development and Reform Commission emphasized the pillar position of the real estate industry,which is complementary to many industries.Therefore,China’s economy has a high dependence on the real estate market.However,in recent years,facing multiple pressures such as market downturn and policy regulation,the development of the real estate industry has continued to decline,and the company’s financial risks may further intensify.It is necessary to build an effective financial risk warning model to improve the company’s financial risk prediction ability.Therefore,the purpose of this study is to construct a financial risk warning model for real estate companies based on machine learning methods,providing reference for predicting financial conditions and strengthening risk prevention.This study mainly conducts a case study on Company A based on a qualitative analysis of its financial situation,combined with the early warning results of the model.The specific research process and results are as follows: firstly,from the perspectives of financial activities and financial efficiency,a qualitative analysis of Company A’s financial situation is conducted,and it is found that Company A has financial risk points such as cash flow shortage and large debt volume.Therefore,it is necessary to construct a financial risk early warning model;Secondly,120 real estate listed companies were selected as samples,and based on existing research,financial indicators such as debt paying ability,operational ability,profitability,growth ability,cash flow,as well as non-financial indicators such as corporate governance,internal control,and audit opinion types were selected to construct an early warning indicator system;Once again,preprocess the warning indicators and select 26 warning indicators;From then on,the highly interpretable logistic regression method in machine learning was used to construct a financial risk warning model.The modeling results showed that the model had certain predictive value,and combined with the actual situation of Company A,it was found that the model had certain applicability to Company A;Finally,the model was used to predict the financial situation of Company A in 2022 and 2023.The warning results showed that Company A had a high level of financial risk in 2022,but did not fall into a financial crisis.The financial risk warning value of Company A in 2023 exceeded the threshold,indicating that Company A may fall into a financial crisis;In addition,based on the early warning results and the company’s financial situation,explore the risk causes of Company A and propose risk prevention suggestions.This study extends the case study of financial risk early warning models for risk warning in specific companies,and also makes up for the shortcomings of more scholars who only choose financial indicators to construct financial risk early warning models for real estate companies,which has certain practical and theoretical significance.