An Early Warning Model of Financial Distress Sharia Banks in Indonesia

Fadhil Yamaly, Sulastri, Syamsurijal Kadir, Isnurhadi

2018

Abstract

Predictive models of financial distress presented by highly qualified researchers have identified conclusively as an early warning of financial distress. This study aims to develop a model of an early warning before the onset of financial distress in the group of Islamic or Sharia banks in Indonesia. Approach to the development of models using multiple discriminant analysis (MDA) on panel data of 11 companies studied Islamic banks in the period 2013-2017. The results showed that the financial variable flow cycle (FFC), Cash Conversion Cycle (CCC) and Debt to Equity could be a differentiator. The discriminant model can predict cases accurately at 81,8%. The study's findings provide empirical support to the stakeholder in the identification of the financial distress in Sharia banks.

Paper Citation

in Harvard Style

Yamaly F., Sulastri., Kadir S. and Isnurhadi. (2018). An Early Warning Model of Financial Distress Sharia Banks in Indonesia.In Proceedings of the 4th Sriwijaya Economics, Accounting, and Business Conference - Volume 1: SEABC, ISBN 978-989-758-387-2, pages 723-732. DOI: 10.5220/0008444507230732

in Bibtex Style

@conference{seabc18,
author={Fadhil Yamaly and Sulastri and Syamsurijal Kadir and Isnurhadi},
title={An Early Warning Model of Financial Distress Sharia Banks in Indonesia},
booktitle={Proceedings of the 4th Sriwijaya Economics, Accounting, and Business Conference - Volume 1: SEABC,},
year={2018},
pages={723-732},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008444507230732},
isbn={978-989-758-387-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th Sriwijaya Economics, Accounting, and Business Conference - Volume 1: SEABC,
TI - An Early Warning Model of Financial Distress Sharia Banks in Indonesia
SN - 978-989-758-387-2
AU - Yamaly F.
AU - Sulastri.
AU - Kadir S.
AU - Isnurhadi.
PY - 2018
SP - 723
EP - 732
DO - 10.5220/0008444507230732