Predicting Corporate Green Sukuk Rating

Green sukuk is a growing asset class within the domain of Islamic finance that emerged as a key player in funding of green and sustainable and responsible environment friendly assets. The emergence of Green sukuk marks an important milestone in Islamic finance that has brought congruence between the conventional, sustainable, responsible investment market and Islamic finance. Green sukuk benefits the economy, environment and society simultaneously. However, the development of Green sukuk brings in additional challenges for the credit rating industry due to the green aspects and shariah compliant nature of the sukuk. Hence in this research, we have explored and analyzed the available frameworks available for green sukuk. We have also proposed a comprehensive rating methodology that incorporates credit default rating with other aspects inherent in green sukuk. We also provide insight to the overall market development in Green Sukuk. In addition to the proposed rating methodology for green sukuk, in this paper we also demonstrate the use of statistical and machine learning techniques in predicting real world credit rating grade for asset based sukuk. We consider several approaches available in the literature for respective techniques and find random Forest and neural networks to be best algorithms in the predicting sukuk rating grade for asset based sukuk. This is both exploratory and conceptual in nature, therefore further studies can be done to develop this subject matter.