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Application of Support Vector Machine Algorithm in Automated Lending Protocols for Decentralized Finance Platforms
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Author(s): C. V. Suresh Babu (Hindustan Institute of Technology and Science, India), Sudhir M. (Hindustan Institute of Technology and Science, India), George Kishore L. (Hindustan Institute of Technology and Science, India)and Sanjay Kumar V. (Hindustan Institute of Technology and Science, India)
Copyright: 2024
Pages: 20
Source title:
Decentralized Finance and Tokenization in FinTech
Source Author(s)/Editor(s): Luan Vardari (University "Ukshin Hoti" Prizren, Kosovo)and Isuf Qabrati (University "Ukshin Hoti" Prizren, Kosovo)
DOI: 10.4018/979-8-3693-3346-4.ch001
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Abstract
The chapter delves into the application of the support vector machine (SVM) algorithm within automated lending protocols for decentralized finance (DeFi) platforms. It begins by outlining the landscape of decentralized lending and borrowing, highlighting the transformative nature of blockchain technology and smart contracts in eliminating intermediaries. Objectives encompass assessing protocol security, scalability, and regulatory implications, along with exploring socio-economic impacts. Theoretical underpinnings, including blockchain, smart contracts, economic incentives, and game theory, inform the discussion, emphasizing the role of SVM in enhancing algorithmic decision-making processes. Through SVM, these platforms can optimize risk management, interest rates, and liquidity provision, thus bolstering financial inclusivity and stability. The chapter concludes with key findings underscoring the pivotal role of SVM in advancing DeFi's core principles of transparency, efficiency, and decentralization.
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