Delve into Innovations in Peer-to-Peer lending and Conventional Funding
Year: 2024
Type: article
Abstract: Purpose :This research explores how digital transformation redefines conventional funding and peer-to-peer (P2P) lending in the evolving financial landscape. The study aims to analyse the impact of cutting-edge technologies such as blockchain, artificial intelligence (AI), and sophisticated algorithms on these financial sectors, identifying key factors and challenges that will shape the future of finance. Methodology : In descriptive research, the focus is on detailing the characteristics of a population or phenomenon through non-interventionist methods, often using surveys or observational studies. Data collection typically involves structured surveys or questionnaires featuring closed-ended questions, which can be administered through various in-person and online channels. The study often employs non-probability sampling techniques, such as convenience sampling. Findings : The study finds that P2P lending platforms, leveraging blockchain and AI, offer innovative alternatives to conventional funding by improving risk assessment, streamlining operations, and enhancing entrepreneur engagement. Meanwhile, traditional financial institutions increasingly adopt digital strategies to enhance credit evaluation, transactional transparency, and digital banking services. The research identifies both opportunities and challenges posed by digital transformation, emphasising its potential to foster innovation, resilience, and long-term growth in the financial sector. Originality :This study contributes insights into how blockchain and AI drive innovation and operational efficiency in P2P lending and traditional financial institutions. It highlights the strategic importance of these technologies in reshaping the financial landscape and provides practical advice for entrepreneurs navigating digital transformation.
Authors: Mrs. Saranya. K, Dr. Madhavaiah Chendragiri, Mr. Bonamukkala Venkatarami Reddy
Institution: Pondicherry University
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6893250015
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