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Development of an AI-Driven Phishing Financial Fraud Detection Platform

Student: Lagunes cuevas Yabin alejandro

Supervisor: Sergey Shershakov

Faculty: Faculty of Computer Science

Educational Programme: System and Software Engineering (Master)

Year of Graduation: 2024

The article is devoted to the aspects associated with the heightened susceptibility of the financial sector, which is currently facing a significant threat from phishing attacks. Financial organisations are increasingly vulnerable to phishing attack methods. While in Russia, the challenge is compounded by sanctions restricting access to global cybersecurity resources. This underscores the need for a robust localised solution to address these digital threats. The author explores the integration of AI in a platform aimed to enhance cybersecurity by developing a platform for the financial sector. In addition, it explains to what extent phishing attacks are harmful, emphasising the importance of user satisfaction, aimed to leverage the risks associated with financial cybersecurity. In conclusion, the following work proposes a new platform, enhancing current detection capabilities of emails, SMS, URLs, and websites, providing financial institutions with a detailed and holistic view of phishing threats, and aiding in strategic decision-making and risk management.

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