Big Data, Artificial Intelligence and Machine Learning: A Transformative Symbiosis in Favour of Financial Technology

C. Stasinakis, G. Sermpinis
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引用次数: 3

Abstract

The financial technology revolution is a reality, as the financial world is gradually transforming into a digital domain of high-volume information and high-speed data transformation and processing. The more this transformation takes place, the more consumer and investor behaviour shifts towards a pro-technology attitude of financial services offered by market participants, financial institutions and financial technology companies. This new norm is confirming that information technology is driving innovation for financial technology. In this framework, the value of big data, artificial intelligence and machine learning techniques becomes apparent. The aim of this chapter is multi-fold. Firstly, a multidimensional descriptive analysis is shown to familiarise the reader with the extent of penetration of the above in the financial technology road-map. A short non-technical overview of the methods is then presented. Next, the impact of data analytics and relevant techniques on the evolution of financial technology is explained and discussed along with their applications’ landscape. The chapter also presents a glimpse of the shifting paradigm these techniques bring forward for several fintech related professions, while artificial intelligence and machine learning techniques are tied with the future challenges of AI ethics, regulation technology and the smart data utilisation.
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大数据、人工智能和机器学习:有利于金融科技的变革共生
金融科技革命已经成为现实,金融世界正逐步向海量信息、高速数据转换和处理的数字领域转变。这种转变发生得越多,消费者和投资者的行为就越倾向于对市场参与者、金融机构和金融科技公司提供的金融服务持支持科技的态度。这一新规范证实了信息技术正在推动金融技术的创新。在这个框架下,大数据、人工智能和机器学习技术的价值变得显而易见。本章的目的是多方面的。首先,本文展示了多维描述性分析,以使读者熟悉上述在金融科技路线图中的渗透程度。然后对这些方法进行简短的非技术概述。接下来,解释和讨论了数据分析和相关技术对金融技术发展的影响,以及它们的应用前景。本章还介绍了这些技术为几个金融科技相关职业带来的转变范例,而人工智能和机器学习技术与人工智能伦理、监管技术和智能数据利用的未来挑战联系在一起。
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