A Fintech-Based Zakat Model Using Artificial Intelligence

Mustafa Raza Rabbani (), M. Kabir Hassan, Shahnawaz Khan () and Aishath Muneeza ()
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Mustafa Raza Rabbani: University of Bahrain
Shahnawaz Khan: Bahrain Polytechnic
Aishath Muneeza: International Centre for Education in Islamic Finance

A chapter in FinTech in Islamic Financial Institutions, 2022, pp 49-63 from Springer

Abstract: Abstract The COVID-19 pandemic and its associated lockdown have created a mammoth economic cost to the economies around the globe. The policy response to the crisis must be fast, secure, and sustainable. It has also created astonishing solidarity among the people with every element of society irrespective of race, caste, creed, or religion working together to save humanity. To overcome the financial and economic disruption caused by the pandemic, it needs immediate attention from the economists and policymakers. Islamic finance has many financial instruments for helping the poor by alleviating poverty, distributing income fairly, and improving social welfare, they comprise, Zakat, Sadaqat, Awqaf, etc. Zakat is the compulsory contribution from the Muslims to the poor and needy every year. Zakat is the compulsory donation from the rich and able Muslims which must be given to the poor and needy within a year. This immediate benefit of Zakat is well suited to tackle an economic crisis such as the one caused by COVID-19. Islamic finance in combination with the Fintech-based technologies like AI, Blockchain, machine learning, and natural language processing can work wonders in achieving Islamic finance objectives. The present study proposes an AI-based Islamic Fintech model to helping the needy and poor affected due to COVID-19. The model uses AI and NLP-based Fintech model for collection and dissemination of Zakat money to needy, poor, COVID-affected, and vulnerable sections of the society.

Keywords: Fintech; Islamic banks; Covid-19; Financial inclusion; Islamic economics; Coronavirus; Zakat (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-14941-2_3

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DOI: 10.1007/978-3-031-14941-2_3

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