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All Journal Akurasi : Jurnal Studi Akuntansi dan Keuangan
Syaima, Novita Widia
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Economics, Econometrics & Finance

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TAX RISK AND CREDIT RATING: A MACHINE LEARNING APPROACH TO PREDICTING CREDITWORTHINESS Syaima, Novita Widia; Rachmawati, Nurul Aisyah
Akurasi : Jurnal Studi Akuntansi dan Keuangan Vol 8 No 1 (2025): Jurnal Studi Akuntansi dan Keuangan, Juni 2025
Publisher : Faculty of Economics and Business University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/akurasi.v8i1.662

Abstract

A credit rating evaluates a company's likelihood of default, creditworthiness, and ability to repay debt. The greater the company's risk, including tax risk, the lower its credit rating. This research explores whether tax risk can affect a company's credit rating. The population in this study are companies listed on PT Pemeringkat Kredit Indonesia (PEFINDO) and the Indonesian Stock Exchange in 2020-2022. This research used purposive sampling and collected 185 samples. According to the study, tax risk adversely and considerably impacts credit ratings. This suggests that a company's credit rating may be lowered by significant tax risk. These findings suggest that increased tax risk may lower a company's creditworthiness. This study can help creditors assess companies' creditworthiness based on these findings. For tax regulators, credit ratings can be used as a basis for conducting tax audits for taxpayers at risk.
Co-Authors Rachmawati, Nurul Aisyah