The reform of the forest tenure system has made the use or ownership of forest resources on the market a factor of production, which has given birth to the reform of the forest investment and financing system, thereby expanding the financing channels for forest farmers. Under such circumstances, forest rights mortgage loans have been gradually launched in various places as an innovative product to improve the forest market. The establishment of the loan company can not only effectively solve the problems of mortgage loans and forest financing difficulties, promote the rapid growth of forest economy, promote the income and wealth of forest farmers, but also bring new opportunities for market development. This paper analyzes the risk management of forest lease mortgage loans based on the K-means grouping algorithm, and aims to analyze the management situation, methods and market of forest lease mortgage loans in order to establish a complete risk management system and extend the risk period. Forest mortgage project. The ability to identify and resolve risks and promote their sustainable development. By using the K-means grouping algorithm, research and experiment on mortgage agents, purchases, etc. The experimental results show that 90% of the factors that affect the risk management of forest mortgage loans are weighted. In order to strengthen the reasonable management of forest mortgages, it needs to be improved gradually.

Yu Yu and Ling Zhang. Forest Property Mortgage Loan Risk Management based on K-means Clustering Algorithm. International Journal of Big Data Intelligent Technology (2020), Vol. 1, Issue 2: 15-24. https://doi.org/10.38007/IJBDIT.2020.010202.

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