A Survey of Trendy Financial Sector Applications of Machine and Deep Learning

Conference paper

Lestari, Nur Indah, Hussain, Walayat, Merigo, Jose and Bekhit, Mahmoud. (2023). A Survey of Trendy Financial Sector Applications of Machine and Deep Learning. Second EAI International Conference, BigIoT-EDU 2022. Switzerland: Springer Nature. pp. 619-633 https://doi.org/10.1007/978-3-031-23944-1_68
AuthorsLestari, Nur Indah, Hussain, Walayat, Merigo, Jose and Bekhit, Mahmoud
TypeConference paper
Abstract

In the field of finance, machine learning encompasses a number of disciplines, including pattern recognition, financial econometrics, statistical computing, probabilistic programming, and dynamic programming. Machine learning (ML) is causing a revolution in the financial industry as more and more companies use ML-automated operations to make better decisions, increase productivity, and achieve other business goals. Machine learning algorithms are being utilised by financial institutions, including banks, fintech companies, insurance brokers, and other suppliers of financial services, in order to forecast financial risk, automate repetitive processes, and gain real-time investment advice. Because of the very nature of their operations, financial institutions generate enormous amounts of data that are often complex. This creates the ideal setting for machine learning, which requires vast datasets from which machines can learn. This research investigates the impact of machine learning, deep learning, and statistical approaches on key financial principles, including fraud detection, money laundering prevention, and credit risk assessment. To investigate the impact of these methodologies on financial indicators, secondary data sources such as books and peer-reviewed journals were analysed.

KeywordsComputer Applications; Information Systems and Communication Service; Artificial Intelligence; Computer Systems Organization and Communication Networks
Year01 Jan 2023
PublisherSpringer Nature
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-031-23944-1_68
Web address (URL)https://link.springer.com/chapter/10.1007/978-3-031-23944-1_68
Journal citationpp. 619-633
Book titleApplication of Big Data, Blockchain, and Internet of Things for Education Informatization
Page range619-633
ISBN978-3-030-87903-7
Web address (URL) of conference proceedingshttps://link.springer.com/book/10.1007/978-3-031-23944-1
Output statusPublished
Publication dates
Print12 Jan 2023
Publication process dates
AcceptedDec 2022
Deposited13 Sep 2024
Additional information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2023.

Place of publicationSwitzerland
Edition1
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