The impact of Indonesian financial accounting standard implementation, credit risk, and credit restructuring on allowance for credit losses in Indonesia

This study aims to investigate the impact of social distancing policies on SMEs in Indonesia. It used a quantitative method with a survey design. Respondents were all SMEs in Indonesia that are affected by social distancing policies during the COVID-19 pandemic. It involved a total of 587 SME samples selected randomly. The data were collected through observations, questionnaires, and literature studies. The collected data were analyzed using descriptive statistics with SPSS software to determine the mean value. The result showed that social distancing policies affect SMEs during the COVID-19 pandemic. This is indicated by the decreasing income and demand for SMEs products, and even some have no income (mean values of 2.40) due to the social distancing policies. Besides, the policy’s impact is also shown in the increasing cost of raw materials and production costs due to supply chain problems (mean values of 4.79). The policy’s impact raises anxiety for SMEs to survive so that business actors change their plans by utilizing information technology (mean values of 4.81). This change is a strategy to survive due to the impact of the applied policies. Although social distancing policies affect SMEs’ survival during the pandemic, research findings show that SMEs in Indonesia did not terminate employment (mean values of 4.37) due to the presence of economic stimulus policies that helped SMEs survive and grow during the COVID-19 pandemic.

In this research, the authors proposed a new method to evaluate borrowers’ credit risk and quality of financial statements information provided. They use qualitative and quantitative criteria to measure the quality and the reliability of its credit customers. Under this statement, the authors evaluate 35 features that are empirically utilized for forecasting the borrowers’ credit behavior of a Greek Bank. These features are initially selected according to universally accepted criteria. A set of historical data was collected and an extensive data analysis is performed by using non parametric models. Our analysis revealed that building simplified model by using only three out of the thirty five initially selected features one can achieve the same or slightly better forecasting accuracy when compared to the one achieved by the model uses all the initial features. Also, experimentally verified claim that universally accepted criteria can’t be globally used to achieve optimal results is discussed.

The study aims to synthesize the challenges that retailers are facing during the COVID-19 emergency. The research is definitive, informative, and based on a single design of cross-sectional research. Quantitative data based on the research instrument were produced (a questionnaire). Five hundred responses were collected from employees of major retail stores in India. Retailer performance is considered a dependent variable, whereas employee well-being, customer and brand protection, use of technology, government policies, and supply chain are used as independent variables. The current study results indicated that employee well-being and government policies have a significant positive impact on retailer performance, while customer and brand protection, use of technology, and supply chain have a significant positive impact on retailers’ performance. This study will help retailers develop strategies for their employees to protect them and understand that technology is needed in the new normal times. This study highlights the need to be flexible in executing strategic strategies, but retailers need to develop comprehensive action plans, including selecting managers of initiative and defining goals and deadlines. Provided that retailers’ current reality is different from the old normal, no time is lost in taking audacious action.