This book aims to provide first-hand information for readers who are concerned about inclusive finance and sustainable development by summarizing China’s policy measures and practical innovations in the development of inclusive finance and expects to provide China’s experience for the development of inclusive finance in more regions. From a worldwide perspective, a large number of people had been excluded from formal financial services for a long time due to various factors. Even in developed economies with sound financial systems, relatively disadvantaged groups are often denied access to effective financial services. In 2005, the United Nations proposed the concept of Inclusive Finance, emphasizing the extension of financial services to less developed regions and low-income groups in society at an affordable cost by improving financial infrastructure and providing them with reasonably priced and convenient financial services. In 2015, the United Nations adopted the 2030 Agenda for Sustainable Development, making inclusive finance an important focus for achieving sustainable development. It has become a global consensus to vigorously develop inclusive finance. China has attached importance to improving financial services for disadvantaged groups such as rural residents, micro-, small and medium enterprises (MSMEs) and others. In 2013, Developing “Inclusive Finance” became China’s national strategy. In 2015, China formulated the Plan for Promoting the Development of Inclusive Finance (2016-2020). In 2016, during its presidency of the Global Partnership for Financial Inclusion (GPFI), China proposed the issue of "Digital Financial Inclusion" and issued the G20 High-level Principles for Digital Financial Inclusion at the G20 Hangzhou Summit in the same year. Through policy guidance and active practice by the financial sector, China has gradually formed a unique development model of inclusive finance and achieved remarkable successes. Physical outlets, service machines and online service channels have been improved, and basic financial services have generally covered both urban and rural areas. The financial services for rural households and MSMEs have improved significantly. The efficiency and convenience of financial services have been significantly improved, and the satisfaction of financial services has significantly increased. China's experience in inclusive finance has been recognized by the international community. In 2017, five cases from China were selected in the G20 report on Digital Financial Inclusion: Emerging Policies and Approaches.

This book starts from the application scenarios of artificial financial intelligence regulation, commercial banking, wealth management and payments, etc., and makes a detailed study of the main scenarios of the application of China's artificial intelligence in the financial field, and also analysis specific application cases of China.With the popularization of smart phones and the rapid development of e-commerce, mobile payment, big data and other technologies are in the ascendant in China in recent years. In particular, artificial intelligence technologies in the form of facial, speech and semantic recognition are showing preliminary advantages in the field of FinTech, and the future era of Intelligent Finance has quietly come. The Chinese government has clearly put forward "China should rely on a robust cycle of domestic demand and innovation as the main driver of the economy while maintaining foreign markets and investors as a second engine of growth", science and technology innovation is the basic motivation of economic and social cycle, to implement the " dual circulation strategy ", it is necessary to understand the key role of scientific and technological innovation in financial innovation services, and improve financial services must be driven by science and technology. There is a natural relationship between artificial intelligence and financial services, because financial services are credit and information intermediaries, and data is the most critical for finance, while artificial intelligence has a super ability in dealing with complex data. At present, many Chinese Banks have applied artificial intelligence to their daily operations and management, such as accurate customer identification, enhanced process tracking, intelligent marketing, and product process transformation, so as to simplify financial service processes and shorten service cycles. In General, this book both pays attention to practical application and theoretical, which is a useful reference book in theoretical research and practical work, and also helps readers to understand the application of intelligent finance in China.

This book proposes a method to solve land use problems, and has made some significant contributions to the land use analysis and optimization study fields. Firstly, three spatio-temporal logit models for land use change analysis, namely, geographically and temporally weighted logit model (GTWLM), spatio-temporal panel logit model (ST-PLM) and generalized spatio-temporal logit model (GSTLM), are proposed. GTWLM, which considers spatio-temporal non-stationarity, includes temporal data in a spatio-temporal framework by proposing a spatiotemporal distance. ST-PLM incorporates the spatio-temporal correlation and individual effect in one model. By integrating GTWLM and ST-PLM, the GSTLM explores spatio-temporal non-stationarity and correlations simultaneously, whilst considering their individual effects to construct an integrated model. Secondly, a MOO-based two-level spatial planning of land use is proposed. The spatial planning aims at managing and coordinating the land use at different geographic extents and involves spatial layouts and structures of land use at different levels. In spatial planning, GIS and Remote Sensing are used to evaluate, analyze, and measure environmental, economic and social issues. The quantitative relationships between these objectives and spatial land use allocation are then used as rules in the MOO process to simulate environmental conditions under different spatial land use allocation scenarios. The book features a case study of Shenzhen city, the most important Special Economic Zone in China. This book will be of interest to academics and professionals in the fields of urban planning, land resource management, remote sensing and geographic information systems.

This book proposes a method to solve land use problems, and has made some significant contributions to the land use analysis and optimization study fields. Firstly, three spatio-temporal logit models for land use change analysis, namely, geographically and temporally weighted logit model (GTWLM), spatio-temporal panel logit model (ST-PLM) and generalized spatio-temporal logit model (GSTLM), are proposed. GTWLM, which considers spatio-temporal non-stationarity, includes temporal data in a spatio-temporal framework by proposing a spatiotemporal distance. ST-PLM incorporates the spatio-temporal correlation and individual effect in one model. By integrating GTWLM and ST-PLM, the GSTLM explores spatio-temporal non-stationarity and correlations simultaneously, whilst considering their individual effects to construct an integrated model. Secondly, a MOO-based two-level spatial planning of land use is proposed. The spatial planning aims at managing and coordinating the land use at different geographic extents and involves spatial layouts and structures of land use at different levels. In spatial planning, GIS and Remote Sensing are used to evaluate, analyze, and measure environmental, economic and social issues. The quantitative relationships between these objectives and spatial land use allocation are then used as rules in the MOO process to simulate environmental conditions under different spatial land use allocation scenarios. The book features a case study of Shenzhen city, the most important Special Economic Zone in China. This book will be of interest to academics and professionals in the fields of urban planning, land resource management, remote sensing and geographic information systems.

This book starts from the application scenarios of artificial financial intelligence regulation, commercial banking, wealth management and payments, etc., and makes a detailed study of the main scenarios of the application of China's artificial intelligence in the financial field, and also analysis specific application cases of China.With the popularization of smart phones and the rapid development of e-commerce, mobile payment, big data and other technologies are in the ascendant in China in recent years. In particular, artificial intelligence technologies in the form of facial, speech and semantic recognition are showing preliminary advantages in the field of FinTech, and the future era of Intelligent Finance has quietly come. The Chinese government has clearly put forward "China should rely on a robust cycle of domestic demand and innovation as the main driver of the economy while maintaining foreign markets and investors as a second engine of growth", science and technology innovation is the basic motivation of economic and social cycle, to implement the " dual circulation strategy ", it is necessary to understand the key role of scientific and technological innovation in financial innovation services, and improve financial services must be driven by science and technology. There is a natural relationship between artificial intelligence and financial services, because financial services are credit and information intermediaries, and data is the most critical for finance, while artificial intelligence has a super ability in dealing with complex data. At present, many Chinese Banks have applied artificial intelligence to their daily operations and management, such as accurate customer identification, enhanced process tracking, intelligent marketing, and product process transformation, so as to simplify financial service processes and shorten service cycles. In General, this book both pays attention to practical application and theoretical, which is a useful reference book in theoretical research and practical work, and also helps readers to understand the application of intelligent finance in China.