As the fintech industry continues to transform into a digital asset payment system and the financial sector relies more on digital systems in general, personal and proprietary data have become prime targets for cybercriminals. Financial firms acquire and process massive volumes of sensitive data, which is collected, stored, and used within their systems, sometimes shared with third and fourth parties. To prevent data breaches in fintech and in other financial firms, various machine learning and artificial intelligence techniques for managing large and complex financial data have been developed.
This Research Topic aims to promote research into emerging technologies that try to ensure confidentiality and data privacy in the financial system, including various digital asset systems, as well as advancing research and discussion about how to mitigate security threats using artificial intelligence. The objective is to present modern machine learning data analysis methods in contextual financial data science, analytical business intelligence, systematic investment strategies, natural language processing for ESG investing, financial monitoring process automation in corporate finance, enhanced customer relations by chatbots, customer engagement and the Internet of Things (IoT), security analysis and portfolio management by robo-advisor, algorithmic trading and high-frequency trading fraud detection, online lending platforms and credit scoring, risk management and prevention, unstructured and big data analysis, trade settlement process automation, asset valuation and management, a Research Topic in Frontiers in Artificial Intelligence (IF 4.0, CiteScore 3.9), and the section on Artificial Intelligence in Finance, a Scopus and Web of Science ESCI (Emerging Science Citation Index) indexed journal.
This Research Topic invites papers on AI, data mining, sentiment analysis and fuzzy logic applied to the following topics:
• Asset Pricing / Investments
• Behavioral Finance
• Blockchain
• Corporate Finance
• Cryptocurrencies
• Cybersecurity
• Digital assets
• Data Privacy
• Data Protection
• Electronic data interchange (EDI)
• Fintech
• Internet security
• Privacy-enhancing technologies
• Regulatory Compliance Laws
Keywords:
Artificial intelligence, Blockchain, Cybersecurity, Data Protection, Internet security, Regulatory, Compliance Laws, Security
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
As the fintech industry continues to transform into a digital asset payment system and the financial sector relies more on digital systems in general, personal and proprietary data have become prime targets for cybercriminals. Financial firms acquire and process massive volumes of sensitive data, which is collected, stored, and used within their systems, sometimes shared with third and fourth parties. To prevent data breaches in fintech and in other financial firms, various machine learning and artificial intelligence techniques for managing large and complex financial data have been developed.
This Research Topic aims to promote research into emerging technologies that try to ensure confidentiality and data privacy in the financial system, including various digital asset systems, as well as advancing research and discussion about how to mitigate security threats using artificial intelligence. The objective is to present modern machine learning data analysis methods in contextual financial data science, analytical business intelligence, systematic investment strategies, natural language processing for ESG investing, financial monitoring process automation in corporate finance, enhanced customer relations by chatbots, customer engagement and the Internet of Things (IoT), security analysis and portfolio management by robo-advisor, algorithmic trading and high-frequency trading fraud detection, online lending platforms and credit scoring, risk management and prevention, unstructured and big data analysis, trade settlement process automation, asset valuation and management, a Research Topic in Frontiers in Artificial Intelligence (IF 4.0, CiteScore 3.9), and the section on Artificial Intelligence in Finance, a Scopus and Web of Science ESCI (Emerging Science Citation Index) indexed journal.
This Research Topic invites papers on AI, data mining, sentiment analysis and fuzzy logic applied to the following topics:
• Asset Pricing / Investments
• Behavioral Finance
• Blockchain
• Corporate Finance
• Cryptocurrencies
• Cybersecurity
• Digital assets
• Data Privacy
• Data Protection
• Electronic data interchange (EDI)
• Fintech
• Internet security
• Privacy-enhancing technologies
• Regulatory Compliance Laws
Keywords:
Artificial intelligence, Blockchain, Cybersecurity, Data Protection, Internet security, Regulatory, Compliance Laws, Security
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.