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This paper aims to propose a model for democratization of Islamic home financing to tackle the issue of sustainability of homeownership affordability.

A conceptual framework and fractional equity model (FEM) are developed to incorporate big data analytics, artificial intelligence and blockchain technology in an ecosystem for affordability and sustainability of homeownership via the proposed financing model. In addition, the FEM adopts the simulation approach to show its validity in terms of liquidity when compared with traditional home financing. In this regard, this paper is focused on developing and demonstrating the feasibility of a new financing model, rather than testing specific hypotheses or relationships. This is to propose the democratization model for Islamic Home Financing that will not benefit the prospective home buyers without compromising the profitability of the financial institutions.

The findings indicate that the proposed end-to-end solution within the financing ecosystem can lead to more efficient matching market between the buyers and sellers of houses, reduced transaction costs, greater transparency and enhanced efficiency which in the end could lead to lower costs of owning homes and sustained financial resilience among house owners. The findings indicate that the FEM model is able to increase homeownership with more elements of liquidity, marketability and sustainability for homebuyers.

This research highlights the potential of big data and blockchain technology in democratizing Islamic home financing and evidence that the transfer of ownership is possible through tokenization. However, this will require a mature financing environment to adapt the technology for practical application.

The model proposes a solution to propagate shared prosperity among stakeholders such as the house buyers/owners, sellers, investors as well the government agencies. The proposed FEM model provides alternative home financing that is more marketable, flexible and sustainable for households/buyers and financiers.

It is hoped that with the proposed financing ecosystem to promote affordability and sustainability of homeownership via big data analytics, artificial intelligence and blockchain technology can lead to greater financial resilience for homeowners which can then be translated to enhanced well-being, increased productivity and can further promote economic growth.

This research is a concept paper based on academic research and industry collaboration with a technology provider.

This study aims to investigate the dynamic interaction between interest rates and commercial property financing offered by Islamic banks in Malaysia.

The authors use the autoregressive distributed lag (ARDL) cointegration methodology to analyse the short- and long-run effect of the interest rates and rental rates on commercial property financing of Islamic banks in Malaysia between 2010: Q1 and 2018: Q2.

The findings reveal that changes in interest rates affect Islamic commercial property financing. This indicates that Islamic banks still rely on interest rates as a benchmark without fully implementing Islamic rental rates. This corroborates the subsequent finding, where overnight policy rates influence commercial property financing.

Despite the authors’ attempt to provide insights into Islamic commercial property financing, the study is limited to secondary data; further research can use survey information to obtain other details that are not included in this study. Similarly, this study does not cover the operation and financial lease debate in Musharakah Mutanaqisah. Future studies can examine the challenges faced by the financial institution towards implementing rental rates in other emerging and developing countries using a different methodology.

This study is the first to investigate the dynamic changes in overnight policy rates, average lending rates and rental rates on Islamic commercial property financing in Malaysia using ARDL techniques. The authors uncover the research and institutional implications of Islamic commercial property financing rates and provide policy and future research directions coupled with the proposed modified rental rate to be developed.