UJI LANGSUNG DAN TIDAK LANGSUNG TEKNOLOGI DALAM MEMITIGASI RISIKO KREDIT PADA PERBANKAN SYARIAH DI  INDONESIA

L.M. Hasriadi; Wilda Yanti

Authors

L.M. Hasriadi Program Studi Akuntansi, Fakultas Ekonomi dan Bisnis, Universitas Mulawarman Samarinda, Provinsi Kalimantan Timur, Kode pos: 75119, Indonesia
Wilda Yanti Program Studi Administrasi Bisnis, Fakultas Ilmu Sosial dan Ilmu Politik, Universitas Mulawarman, Provinsi Kalimantan Timur, Kode pos: 75411, Indonesia

Keywords:

direct and indirect effects, mitigating credit risk, banking finance

Abstract

The objectives to be achieved in this study are: to determine and test the credit risk management system has a direct and indirect effect on credit portfolio quality, 2) to determine and test the credit risk management system has a direct and indirect effect on credit risk mitigation through credit portfolio quality, to know and test big data has a direct effect on credit portfolio quality, 3) to know and test artificial intelligence and machine learning has a direct and indirect effect on credit portfolio quality.4) to know and test the credit process automation has a direct and indirect effect on credit portfolio quality. ) identify and test the direct and indirect effect of credit process automation on credit portfolio quality, 5) identify and test the direct effect of credit portfolio quality on credit risk mitigation. Novelty. Focus on Credit Risk in Sharia Context, because credit risk has been widely studied in conventional banking, but the focus on Islamic banking with the principles of contracts, profit sharing, and sharia values makes this research specific and contextual. 3) Technology Integration as a Strategic Variable, Research method. This research uses Partial Lesquare (PLS). Using primary data, with a sample of 675. Research findings. This study found that all exogenous variables have a significant direct and indirect effect on endogenous variables, except artificial intelligence and machine learning which have a direct effect on credit risk mitigation. Conclusion. The results of this study can be concluded that of the 13 (thirteen) hypotheses proposed all have a positive and significant direct and indirect effect on Credit Portfolio Quality and Credit Risk Mitigation.

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