Establishing risk assessment system and risk control, enterprises can prevent and mitigate risks and minimize losses caused by risks. On the basis of reviewing related literature of financial risk measurement with solvency, profitability, operation ability and development ability, through the construction of regression model and statistical method, the empirical analysis and inspection are carried out for the listed agricultural companies. According to the financial indicators can alert the financial situation of agricultural companies and reflect the financial risk situation.
Design/methodology/approach: A sample of 20 financial institutions was selected and from each selected, 10 respondents were selected giving a total sample size of 200. The Principal Component Analysis (PCA), with inbuilt ability to check for composite reliability, was used to obtain composite indices for governance indicators as well as the indicators of financial performance, based on the set of questions framed for each of them. Findings: The results revealed that all indicators of corporate governance positively influence the financial performance of financial institutions. However, whereas the effect of auditing and compliance, transparency, disclosure and risk management were found to be significant in their influence on financial performance, board role and composition turns out to be insignificant. As such, policy prescriptions are proposed towards redefining the role of board members while enforcing accountability and transparency. Practical implications: This paper demonstrates the importance of transparency and disclosure in the managerial affairs, the financial performance of financial institutions through loan portfolio, liquidity and profitability increases by 0.4 with such effect being statistically relevant at 1%. Originality/value: The use of primary data in assessing the impact of corporate governance rather than just using secondary data forms the novelty of this study. In addition, we use principal component analysis (PCA) to assess the weight of various parameters.