Title: Machine learning-based P2P lending Islamic Fintech model for small and medium enterprises in Bahrain

Authors: Mustafa Raza Rabbani; Shahnawaz Khan; Mohammad Atif

Addresses: Department of Economics and Finance, College of Business Administration, University of Bahrain, Kingdom of Bahrain ' Faculty of Engineering, Design and Information and Communications Technology, Bahrain Polytechnic, Kingdom of Bahrain ' Department of Commerce and Business Studies, Jamia Millia Islamia, New Delhi, India

Abstract: The study provides the current overview of P2P lending in Bahrain especially for the small and medium enterprises (SME) sector and proposes a machine learning-based Islamic Fintech model for P2P lending. The study also suggests how P2P lending platform (mainly a debt-based platform) can follow sharia principles and can satisfy the needs of customers who believe in lending/borrowing as per Islamic finance. The study proposes an Islamic Fintech model for person to business (P2P) lending suitable for the small and medium enterprises. It is high time that new methods of credit should be introduced and promoted to give a boost to the sector and save hundreds of thousands of jobs. Against such a backdrop, the present study identifies the gaps in lending system for the small and medium enterprises and proposes a machine learning-based Fintech model as per sharia compliance for attracting more lenders.

Keywords: Islamic Fintech; machine learning model; Fintech; small and medium enterprises; SMEs; peer-to-business lending; P2P lending platform.

DOI: 10.1504/IJBIR.2023.130079

International Journal of Business Innovation and Research, 2023 Vol.30 No.4, pp.565 - 579

Received: 11 Apr 2020
Accepted: 03 Feb 2021
Published online: 05 Apr 2023 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article