ABSTRACT
Rural banks with local government ownership as majority shareholders aimed to increase public welfare and earn profits. state-owned banks (also state-owned enterprises (SOEs)) also have agency conflict, which may increase due to increased political content. Post-merger and acquisition (Post-M&A) due to the COVID-19 pandemic increases rural bank risk in lending. The research objective is to determine the impact of increased risk on rural bank lending. Data were collected from 32 annual reports of rural banks in Indonesia. Documentation was used to collect the data. Loan deposit ratio (LDR) is the dependent variable, the risk is the independent variable, and capital adequacy ratio (CAR), net profit margin (NPM), and return on equity (ROE) as the control variables. The technique of analyzing data is an analysis of covariance. The result show banks with below-average risk have a greater difference (0.0393) than above-average risk (0.0347). Another result indicates that LDR is not determined by the bank's health or the business risk of the debtor. Government demands through financing in local government, and it ignores risks and produces risk-taking behavior of managers. The government, as the majority shareholder, has a more effective monitoring role. Corporate social responsibility (CSR) oriented to society demand has been produced from rural banks owned by the government. © 2023 The Authors.
ABSTRACT
The spread of the Covid-19 Virus which has a major impact on various sectors of human life, from health problems that have caused many deaths and also economic impacts. The decline in people's purchasing power has caused the industry to experience a decrease in sales turnover, causing business actors to carry out budget efficiency by terminating employment. In terms of assisting government programs in assisting victims of layoffs, a system for mapping the locations of these victims is needed. In building a mapping system for the location of victims of layoffs using the XP method which is part of agille. The system can display the location area down to the districts level. By using a system of mapping the locations of dismissed communities, it can assist in data collection and distribution of assistance.