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Advances in Machine Learning, IoT and Data Security

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AI-Driven Financial Security: Innovations in Protecting Assets and Mitigating Risks
Authors
Affiliations

1 Department of Business Administration, International American University, Los Angeles, CA 90010, USA

2 Department of Information and Communication Technology, Islamic University, Kushtia -7003 Bangladesh

3 Department of Computer Science and Engineering, Daffodil International University, Birulia, Savar, Dhaka-1216

Author's Details

Name: Mani Prabha

Email: mprabha@iaula.edu

Department: Department of Business Administration

Affiliation Number: 1

Address: Los Angeles, CA 90010, USA

Abstract
The financial sector encounters numerous challenges such as cyber threats, fraud, and regulatory compliance. Traditional methods of safeguarding financial transactions and assets are becoming increasingly insufficient against advanced cyber-attacks. This thesis examines the transformative impact of Artificial Intelligence (AI) on financial security. It investigates various AI-driven innovations, their applications in asset protection, and risk mitigation, while also considering the ethical and regulatory implications. AI is reshaping financial risk management by offering advanced tools and techniques for identifying, assessing, and mitigating risks. This article explores the innovations and applications of AI-driven financial risk management, emphasizing its transformative effect on traditional risk management practices. We discuss various Artificial intelligence technology, such as natural language processing, predictive analytics, and machine learning and their applications in enhancing financial stability, regulatory compliance, and operational efficiency. As cyber threats grow more sophisticated, traditional network security approaches are becoming inadequate due to scalability issues, slow response times, and the inability to detect advanced threats. This highlights the need for research into more efficient security methods to protect against diverse network attacks. Cybercriminals use AI for data poisoning and model theft to automate attacks, emphasizing the need for AI...

Keywords: 

Artificial Intelligence (AI), Financial security, Asset protection, Risk reduction, Network security

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