This book first conducts in-depth research on relevant concepts and summarizes the current research status in this field both domestically and internationally, laying a theoretical foundation for subsequent research. Subsequently, by analyzing the current situation and challenges of financial support in the development of the Internet of Things industry, the mechanism of financial support for the development of the Internet of Things industry was deeply explored, and corresponding policy recommendations were proposed. On this basis, this book focuses on the application of machine learning and big data in credit risk assessment. By sorting out traditional credit risk assessment methods, the advantages and limitations of machine learning based credit risk assessment methods were compared and analyzed. At the same time, we also delved into the application of big data in credit risk assessment models, demonstrating how big data can help improve the accuracy and efficiency of risk assessment. It is worth mentioning that this book also focuses on the application of Internet of Things technology in credit and financial management. Through empirical analysis of the efficiency of financial support for the Internet of Things industry, the enormous potential of Internet of Things technology in improving the efficiency of financial services has been revealed. In addition, the application of Internet of Things technology in commercial bank credit business and how to solve the problem of difficult loans for small and micro enterprises were also discussed. 

This book strives to combine theory with practice, aiming to provide a comprehensive and in-depth perspective for financial practitioners, researchers, and interested readers to understand the application of machine learning and big data in risk assessment of credit IoT financial management. I hope that the publication of this book can promote research and practice in related fields, and contribute to the healthy development of the financial industry. 

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