Assessment of Default Risk on Indonesian Corporate Sukuk Using the Moody’s KMV Model
Abstract
This study examines the probability of default of Corporate Sukuk issuers in Indonesia using the Moody's KMV Model. The increasing development of corporate sukuk in Indonesia has raised concerns regarding issuer solvency and default vulnerability, particularly because many contemporary sukuk structures continue to exhibit asset-based and debt-like characteristics. This study aims to assess the default risk profile of Indonesian corporate sukuk issuers and to evaluate the relevance of the KMV framework in identifying financially distressed issuers. The study employed a quantitative approach using secondary data obtained from audited financial statements, Indonesia Stock Exchange publications, and market data of corporate sukuk issuers. The sample consisted of sukuk ijarah and sukuk mudharabah issuers listed on the Indonesia Stock Exchange, selected using purposive sampling. The probability of default was estimated through the Moody’s KMV framework by calculating firm asset value, asset volatility, Distance to Default (DD), and Expected Default Frequency (EDF). The results indicate that issuers possessing lower asset values and higher asset volatility consistently produced lower DD values and higher EDF values, reflecting a greater probability of default. The findings also show that the repayment capacity of corporate sukuk issuers remains highly dependent on issuer financial stability rather than on the liquidation value of underlying assets. In addition, the KMV framework successfully identified issuers experiencing severe financial distress, particularly PT Berlian Laju Tanker Tbk and PT Tiga Pilar Sejahtera Food Tbk. The study concludes that the KMV framework provides a relevant market-based approach for assessing default risk within the Indonesian corporate sukuk market.
Downloads
References
Mawardi, I., Estetiono, A., Widiastuti, T., Robani, A., Mustofa, M. U. A., Hakim, F. K., Almaulidiyah, Q., & Dewi, E. P. (2026). Hybrid early warning system: Integration of Z-score and machine learning for predicting financial performance of IRB in Indonesia. Journal of Open Innovation: Technology, Market, and Complexity, 12(1). https://doi.org/10.1016/j.joitmc.2025.100694
Merton, R. C. (1974). On the Pricing of Corporate Debt: The Risk Structure of Interest Rates. The Journal of Finance, 29(2), 449–470. https://doi.org/10.1111/j.1540-6261.1974.tb03058.x
Copyright (c) 2026 Mukhamad Ali Yusuf, Rifki Ismail, Erwandi Tarmizi

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.















