Pengaruh Risiko Kredit, Risiko Likuiditas, dan Permodalan terhadap Kinerja Keuangan

This study aims to determine the effect of Credit Risk, Liquidity Risk, and Operational Efficiency on Financial Performance in the Conventional Banking Sector listed on the Indonesia Stock Exchange for the period 2019-2023. The research method used is quantitative using secondary data obtained from the Indonesia Stock Exchange, namely the annual financial reports of conventional banks. The sampling technique was carried out using the purposive sampling method. The analysis was carried out with credit risk using the Net Performing Loan (NPL) ratio, liquidity risk using the Loan to Deposits Ratio (LDR) ratio, operational efficiency using the Operating Expenses to Operating Income (BOPO) ratio and financial performance was measured using Return On Assets (ROA). The results of the study showed that partially the credit risk variable had a significant negative effect on financial performance, liquidity risk did not have a significant effect on financial performance, operational efficiency did not have a significant effect on financial performance. Simultaneously, credit risk, liquidity risk, operational efficiency had a significant effect on financial performance.

This study aims to empirically examine the impact of credit risk, liquidity, and bank size on the financial performance of conventional banks listed on the Indonesia Stock Exchange (IDX) during the period 2014-2023, with a particular focus on the COVID-19 pandemic period. The research variables used include the Non-Performing Loan (NPL) ratio, Loan to Deposit Ratio (LDR), and bank size, while Return on Assets (ROA) is used as a financial performance indicator. This study uses the purposive sampling method to select a sample from 138 banks listed on the IDX, resulting in 9 banks that meet the established criteria. Data analysis was conducted using panel data regression with the Fixed Effect Generalized Least Square (GLS) model to address the issues of autocorrelation and heteroskedasticity found in classical assumptions. The research results show that credit risk (NPL) has a significant negative impact on ROA, while bank size and liquidity (LDR) have a significant positive impact on ROA during the pandemic. These findings highlight the importance of managing credit and liquidity risks as well as optimizing bank size to improve financial performance amid the challenging economic conditions caused by the pandemic. This study also suggests that the financial performance of banks can be more stable if supported by appropriate risk management strategies and good operational efficiency. The limitations of this study include a sample restricted to conventional banks in Indonesia and the specific conditions during the COVID-19 pandemic, which may affect the generalization of the results.

This study aims to determine the effect of inflation, the BI-7 Days Repo Rate, Credit Risk, and Liquidity Risk on the Financial Performance of Conventional Commercial Banks with the 2017-2021 research period. Research objects using 39 conventional commercial banks listed on the Indonesia Stock Exchange using a purposive sampling method. Hypothesis testing using descriptive statistics with multiple linear regression analysis methods. The results indicate that Inflation has a positive effect on financial performance. The BI-7 Day Repo Rate has no effect on financial performance. Credit risk has a negative influence on financial performance. Liquidity risk has no effect on financial performance.

This study discusses the causal relationship between bank corporate governance, capital adequacy and the probability of bank failure due to credit risk from the creditor's perspective on the bank's financial performance. The probability of failure of commercial banks in measuring risk-taking behavior. The special characteristics of commercial banks with smaller board sizes, shareholder equity, and long-term loans are associated with significantly lower levels of credit risk. Larger supervisory boards and short-term debt are associated with lower levels of credit risk.This study aims to examine and prove the effect of corporate governance on capital adequacy, and corporate governance directly and mediated by capital adequacy and credit risk impact on financial performance. Test and prove that corporate governance affects credit risk. Test and prove the effect capital adequacy to credit risk, as well as capital adequacy directly and mediated by credit risk have an impact on financial performance. Test and prove the effect of credit risk on financial performance. The analysis technique uses Generalized Structured Component Analysis (GSCA). The unit of analysis is 30 conventional commercial banks listed on the Indonesia Stock Exchange for the period 2016-2020, using panel data, namely time series and cross sectional data, with a number of observations of 30 x 5 years = 150 financial statements.The findings of this study are expected to contribute to the development of science in the study of financial management, especially the theory of corporate governance and credit risk management, namely: corporate governance as a source of value creation, ensuring capital adequacy as a buffer for the risk of losing credit portfolios and managing credit risk at a minimum level. to maintain financial stability and increase Profit which ensures financial performance remains in good or healthy condition. This study concludes that corporate governance has a significant influence on capital adequacy and financial performance, because good corporate governance will manage an optimal capital structure and the availability of capital adequacy that makes the company more able to operate and invest optimally, so as to generate maximum profit to improve financial performance. The influence of corporate governance on bank financial performance is also mediated by capital adequacy. Corporate governance has no significant effect on credit risk. Corporate governance cannot determine credit risk, because credit risk is the responsibility of company management in order to control risk in banking operations. Capital adequacy has a significant influence on credit risk and financial performance, because capital adequacy for the company's operations and investments will improve the bank's financial performance. Capital adequacy has a direct and mediated effect of credit risk on financial performance. Sufficient capital is able to reduce credit risk and improve financial performance, because credit risk which has a negative impact on financial performance has been successfully reduced. Keywords: Corporate Governance, Capital Adequacy, Credit Risk, Financial Performance. DOI: 10.7176/RJFA/12-20-06 Publication date: October 31 st 2021

This study aims to analyze the influence of capital, credit risk, and liquidity risk on the financial performance of conventional banking companies listed on the Indonesia Stock Exchange (IDX) during the period of 2015-2023. The population used in this study consists of 47 commercial banks listed on the IDX. The sample used in this study includes commercial banks categorized as KBMI 3 (Banks based on Core Capital), which are banks with core capital ranging from IDR 14 trillion to IDR 70 trillion, totaling 10 banks. The type of data used in this study is quantitative data, specifically secondary data from the annual financial reports of commercial banks listed on the IDX for the period 2015-2023. The analytical method used is multiple linear regression. The results of the study indicate that Capital (CAR) does not have a positive effect on financial performance (ROA), Credit Risk (NPL) has a negative effect on financial performance (ROA), and Liquidity Risk (LDR) has a negative effect on financial performance (ROA) in banking companies.

This study aims to examine and explain the effect of intellectual capital and capital adequacy on credit risk and financial performance. Effect of credit risk on financial performance. The study population was 43 with a sample of 31 Commercial Banks that had been listed on the Indonesia Stock Exchange. The observation period from 2012 to 2016. The sampling method was purposive sampling, data of 155 bank financial statements. The data analysis technique uses statistical procedures to test hypotheses with the Generalized Structured Component Analysis (GSCA) software.The finding of this study is that intellectual capital has a negative and significant effect on credit risk. Intellectual capital has a positive and significant effect on financial performance. Capital adequacy has a positive and significant effect on credit risk, and financial performance. Credit risk has a negative and significant effect on financial performance. This study suggests that managers of banks, especially bank go public, pay more attention to the variable intellectual capital in the sense that any additional investment in the 3 IC components (human capital, structural capital and capital employed) can be efficiently used to create value added and increase company value. IC is the only source of value creator in the future, which implicitly utilizes tangible and intangible assets and mitigates risk optimally. Recommendations for further research can expand the general banking sector population in longer research periods to get better results. Keywords : Intelletual capital, capital adequacy, credit risk, financial performance DOI : 10.7176/RJFA/10-10-22 Publication date :May 31 st 2019

This research aims to examine the influence of credit risk, liquidity risk and capital adequacy on financial performance in the conventional banking sector listed on the Indonesian Stock Exchange for the 2021-2023 period. The sampling technique used in this research is Purposive Sampling. The population in this study was 42 companies and 38 companies met the requirements to be the sample. The type of data used in this research is secondary data and multiple linear regression analysis methods. Credit Risk is measured using Non Performing Loans. Liquidity Risk is measured using the Loan to Deposit Ratio. Capital Adequacy is measured using the Capital Adequacy. The financial performance of banking companies is measured using Return On Assets. The Classical Assumption Test states that the data in this study are normally distributed and produce a regression model that is free from multicollinearity, heteroscedasticity and autocorrelation. Based on the partial test analysis, the results obtained are : (1) Credit Risk has a positive and significant effect on Financial Performance. (2) Liquidity Risk has a positive and significant effect on Financial Performance. (3) Capital Adequacy has no significant effect on Financial Performance. And the results of the F Test in this research show that Credit Risk, Liquidity Risk and Capital Adequacy simultaneously influence Financial Performance. The findings in this research have implications for banking companies to pay careful attention to financial management in order to obtain maximum profits.

Due to their erratic financial performance and failure to honour shareholder promises, the Kenyan central bank has formally placed a few commercial banks under receivership. Although commercial banks constantly use thorough risk management procedures, the banking industry nonetheless suffers losses. This results from the banking industry's exposure to risks related to liquidity, credit, interest rates, and foreign exchange rates. The purpose of this research was, thus, to assess the impact of credit, interest rate, and foreign currency rate risks on the return on equity of Kenyan commercial banks. The research study examined how financial risks affect Kenya's commercial banks' profits. The study was founded on agency theory and reinforced by international Fischer's affect theory, liquidity preference theory, and interest rate parity. This study employed a causal analysis approach. The participants in this study comprised all of the 39 commercial banks operating in Kenya between 2017 and 2021. The data collecting sheet was used to compile the secondary data. STATA was used to analyse the data using a panel regression model at a 95% level of significance. Tests for multicollinearity, heteroscedasticity, and normalcy as well as the Hausman test were established. Descriptive statistics such as mean, standard deviation and both the minimum and maximum were used to present the data. The study established that while credit risk had a significant negative impact on commercial banks' performance, liquidity risk had a significant positive benefit. Furthermore, exchange risk improved commercial banks' bottom lines, however, this benefit was not statistically significant. Finally, interest rate risk impacted commercial banks' bottom lines negatively but not statistically significantly. According to the study's findings, commercial bank management should be cautious when lending money to new clients and should evaluate existing customers' credit histories before extending credit. To support failing banks, the report suggested that the government and the Central Bank of Kenya increase the minimum liquidity ratio required by law. The government bank should keep a close eye on commercial banks' liquidity ratios to alert any that are having trouble meeting the minimum statutory requirement. Keywords: Financial Risks, credit risk, liquidity risk, exchange rate risk, interest rate risk, financial performance

This study aims to examine financial risk, namely credit risk, liquidity risk, and operational risk on the financial performance of coal mining sub-sector companies on the Indonesia Stock Exchange in 2016-2020. The sampling technique used purposive sampling to get a total of 54 observations. This type of research is an associative quantitative study with panel data regression analysis techniques. Based on the results of the analysis, it is found that Credit Risk, Liquidity Risk, and Operational Risk have a negative effect on Financial Performance . The lower the risk that occurs will affect the increasing value of the company. The implication of this research is that the company is expected to manage and control the risks in the companys financial activities (credit risk, liquidity risk and operational risk) optimally so that problems do not occur in order to increase the level of profitability. KEYWORDS: Credit Risk, Liquidity Risk, Operational Risk, Financial Performance

This study discusses liquidity risk, credit risk, operational risk, and interest rates risk on finance performance at the National Private Foreign Exchange Commercial Bank listed on the Indonesia Stock Exchange for the period 2013-2017. In this study, the independent variables are liquidity risk, credit risk, operational risk and interest rate risk and the dependent variable is financial performance. The object of research is the National Private Foreign Exchange Private Bank listed on the Indonesia Stock Exchange for the period 2013-2017. The population in this study was 23 banks. The sampling technique using purposive sampling method, based on research criteria, the research sample won 11 banks. The analysis tool used is panel regression data with eviews 6. The data used in this study is secondary data obtained from the official website pages of the Indonesia Stock Exchange and Bank Indonesia. Partially, the results of the study indicate that negative liquidity risk is not significant to finance, negative credit risk is significant to finance, operational risk is significantly negative to financial performance, and interest rates increase significantly positive to finance. Simultaneously liquidity risk, credit risk, operational risk and interest rate risk affect financial performance.

The insurance industry is instrumental in economic growth through enabling protection, capital creation and promoting commerce. However, there has been a decline in the insurance industry's profitability in Kenya. Hence, the study assessed the effect of insurance risks on the financial performance of insurance companies in Kenya. Specifically, the study examined the effects of credit risk, liquidity risk, solvency risk, reinsurance risk and underwriting risk on financial performance of insurance companies in Kenya. GDP was used as a moderating variable. The study was anchored on agency theory, credit risk theory, liquidity preference theory and collective risk theory. The target population included all the 53 licensed insurance companies operating in Kenya since 2015. A census approach was used. Explanatory research design and positivism research philosophy were utilized. Secondary data was gathered from audited financial statements submitted to Insurance Regulatory Authority for the period between 2015 and 2020. With the aid of STATA, panel data was analysed through descriptive statistics, correlation and regression analyses. The multiple regression results revealed that credit risk had a negative significant effect on financial performance, liquidity risk had a negative significant effect on financial performance, solvency risk had a negative significant effect on financial performance and underwriting risk had a negative significant effect on financial performance. But reinsurance risk had a positive insignificant effect on financial performance. GDP growth rate significantly moderates the relationship between the insurance risks and the financial performance of insurance companies in Kenya. The study recommended that insurance companies should have good credit risk management frameworks to minimize credit risks, implement proper investment portfolio management to guard against liquidity risks, in cases of negative asset base, increase the share capital, cover most of their claims themselves but ensure they have adequate reinsurance where high risk investment is involved and put in place proper policy estimation and valuation techniques. Keywords: Credit risk, liquidity risk, solvency risk, reinsurance risk, underwriting risk, GDP, financial performance, insurance companies, Kenya

This study uses GCG self-assessment as a moderating variable to investigate how risk management, in particular operational, credit, and liquidity risk, affects financial performance. utilizing secondary and quantitative data from the websites of the Financial Services Authority (OJK) and each Rural Bank (BPR) for the 2019–2023 timeframe. Purposive sampling was the approach utilized to acquire the study's sample. There are 17 rural banks included in the sample size. The Structural Equation Modeling (SEM) approach and the SmartPLS 3.2.9 analysis tool are used in research data processing. The findings of the study demonstrate that operational risk significantly and negatively impacts financial performance. Liquidity risk has a positive but not significant effect on financial performance, while credit risk has a negative impact. This study also discovered that while GCG self-assessment was able to moderate the association between credit risk and financial performance, it was unable to moderate the relationship between financial performance and operational risk or liquidity risk.

Financial risk if not properly taking care of in a business might lead to its collapse especially, insurance companies whose core business deals with day to day handling of risk, in light of this, the study examined the effect of financial risk on financial performance of listed insurance companies in Nigeria from 2009 to 2018. Population of the study consist of 27 listed insurance companies and a sample size of (19) firms. The study used secondary data obtained from annual report of the firms and Correlational design was used. Financial performance which is the dependent variable measured by return on asset (ROA) while independent variable are credit, liquidity and solvency risks. The results from the fixed effect regression proved that credit risk has negative and significant effect on financial performance, Liquidity risk has negative and insignificant effect on ROA and solvency risk has positive and significant effect on ROA. The study concludes that credit risk has adverse influence on ROA of listed insurance companies in Nigeria. The report advises that Nigerian insurance providers should do better to adequately control their receivable number by supplying their debtors with payment plans that are appropriate for servicing their outstanding debt or loan. Keywords: Financial Performance, Credit risk, Liquidity risk and Solvency risk DOI: 10.7176/EJBM/12-12-13 Publication date: April 30 th 2020

The reserarch aims to determine and test the effect of financial risk on the financial performace of banks (the case study on banks listed on te Indonesian stock exchange). The indicator usud in this reserach is the Return on Assets (ROA) for Financial Performance, Operational Efficiency Ratio (BOPO) for Operational Risk, Capital Adequacy Ratio (CAR) for Capital Risk, Loan to Deposit Ratio (LDR) for Liquidity Risk, dan Non Performing Loan (NPL) for Credit Risk. This study took a sample of banking compies listed in Indonesian Stock exchange from 2016-2020 and the sampling technique using puposive sampling technique. The sample obtained is 6 sample company. The analysis used in this study is analysis panel data regression. The parcial test show that operation risk has negative but not significant effect on financial performance, capital risk has a postive and significant effect on financial performance, liquidity risk has negative but not significant effect on financial performance and credit risk has negative and significant effect on financial performance. Meanwhile, the simultaneous show that the financial risk has significant effect on financial performance.
 Keywords : Financial Performance, Fianancial Risk, Operation Risk, Capital Risk, Liquidity Risk, And Credit Risk

This article is to examine the relationship between net interest margin (NIM) and its determinants: risk averse level, liquidity risk, and credit risk. In addition, the article aims to investigate the moderating role of central bank interest rate on the relationship. We observe 17 Indonesian banks, which are listed on Indonesia Stock Exchange in 2017 – 2021 period. We run panel data regression model with 380 firm-year total observations. The Hausman test suggests that we use Random Effect Model (REM) for the parameter estimation. Our study confirms that NIM is determined by credit risk, liquidity risk, and risk averse level. Other than that, we found that central bank interest rate moderates well the relationship of NIM and its determinants by which the dynamic of the relationship of net interest margin and its determinants can be explained. The presence of the central bank interest rate consistently explains the dynamics of the relationship between NIM, risk averse level, liquidity risk, and credit risk. Our model accommodates the positive/negative relationship of NIM and its determinants: credit risk, liquidity risk, and risk averse level. These findings are expected to shed light on the mixed and inconsistent findings of previous research. The ongoing impact of the central bank interest rate consistently elucidates the dynamics between NIM, risk aversion level, liquidity risk, and credit risk. These findings are expected to bring clarity to the mixed and inconclusive results observed in prior research.