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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 contains high-quality papers presented at the First International Forum on Financial Mathematics and Financial Technology.

This book introduces the novel artificial intelligence technique of polymodels and applies it to the prediction of stock returns. The idea of polymodels is to describe a system by its sensitivities to an environment, and to monitor it, imitating what a natural brain does spontaneously. In practice this involves running a collection of non-linear univariate models. This very powerful standalone technique has several advantages over traditional multivariate regressions. With its easy to interpret results, this method provides an ideal preliminary step towards the traditional neural network approach. The first two chapters compare the technique with other regression alternatives and introduces an estimation method which regularizes a polynomial regression using cross-validation. The rest of the book applies these ideas to financial markets. Certain equity return components are predicted using polymodels in very different ways, and a genetic algorithm is described which combines these different predictions into a single portfolio, aiming to optimize the portfolio returns net of transaction costs. Addressed to investors at all levels of experience this book will also be of interest to both seasoned and non-seasoned statisticians.