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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.
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