Özet:

The purpose of this research was to examine the direct and indirect effects of non-financial information on the Probability of Default (PD). Financial information was used to mediate this relationship with Size and Age as control variables. Furthermore, the non-financial information consisted of Corporate Governance (CG) variables, Research and Development (R&D), Market Information, and Macro Factors. Financial Performance (FP) included Current Ratio (CR), Total Asset Turn Over (TATO), Debt to Equity (DAR), and Return on Assets (ROE).This research used a simultaneous panel model approach, while the linear and logistic regression was determined throughdiscriminant analysis. Data were collected from 19 manufacturing companies listed on the Indonesia Stock Exchange from 2009 to 2018. Importantly, the novelty of this research was the inclusion of R&D and Financial Performance as mediating variables.In the first stage of linear regression, Financial Performance was significantly influenced by Corporate Governance, R&D, and Market Information. The macro factor with a significant effect was interest, while R&D reduced Financial Performance. The second stage of logistic regression with Probability of Default as the dependent variable had a significant influence on Financial Performance, Corporate Governance, and Market Information. After mediation by Financial Performance, R&D and macro interest factors significantly influenced the Default Probability.The novelty of this research was the inclusion of R&D and Financial Performance as mediating variables.This research showed that companies should always pay attention to Financial Performance (FP) ratios to avoid default, especially in CR and DAR that have the opportunity to Profitabilities Default (PD). Creditors may easily detect the health condition of the company by constantly monitoring and evaluating Corporate Governance (CG) and FP on PD.This research is limited to direct and indirect effects through Financial Performance as a mediation on the Default Probability.Therefore, further research is recommended to make comparisons per sub-sector with the lag variable in R&D.

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