Risk Control Analysis Research Articles

An analysis of risk control in the financial sector using big data technology

The rapid development of information technology has ushered in a new era of big data in the financial industry, which has provided financial institutions with a plethora of novel tools for risk management, while also playing a pivotal role in the industry's risk control landscape. This paper analyzes the public data of existing financial institutions, combines relevant literature, and employs big data technology to assess and identify risks, which aims to explore how big data technology can improve the risk management ability of the financial industry. In addition, the paper examines the challenges and problems faced by big data technology in the application of financial risk control, including data privacy and security, technology costs, and the demand for specialized talents. The research demonstrates that big data technology improves the speed and accuracy of risk identification, but also points out the challenges of data privacy and security management. Future risk control models need to better integrate big data analytics with traditional risk management methods, thus promoting the further development and application of big data technology in the field of risk control.

Analysis of Risk Control in College Sports Based on Big Data Technology

Analysis of Risk Control in College Sports Based on Big Data Technology

Failure mode and effect analysis in human islet isolation: from the theoretical to the practical risk

ABSTRACT This study aimed to assess the global mapping risk of human islet isolation, using a failure mode and effect analysis (FMEA), and highlight the impact of quality assurance procedures on the risk level of criticality. Risks were scored using the risk priority number (RPN) scoring method. The risk level of criticality was made based on RPN and led to risk classification (low to critical). A raw risk analysis and a risk control analysis (with control means and quality assurance performance) were undertaken. The process of human islet isolation was divided into 11 steps, and 230 risks were identified. Analysis of the highest RPN of each of the 11 steps showed that the 4 highest risks were related to the pancreas digestion and islet purification stages. After implementation of reduction measures and controls, critical and severe risks were reduced by 3-fold and by 2-fold, respectively, so that 90% of risks could be considered as low to moderate. FMEA has proven to be a powerful approach for the identification of weaknesses in the islet isolation processes. The results demonstrated the importance of staff qualification and continuous training and supported the contribution of the quality assurance system to risk reduction.

Risk control analysis of a furniture production activities using hazard identification and risk assessment method

The furniture industry in Indonesia is growing rapidly that leads to technological development. But the use of technology in the industry creates some risk to worker safety. The number of work accidents in Indonesia at the end of 2016 is relatively high. Therefore, this research is conducted to identify hazards and determine risk control using hazard identification and risk assessment method (HIRA). There are three main stages, i.e. identify and analyze hazards, classify hazards and risk control. The result shows that there are nine potential hazards in furniture production, 22% of it is categorized as high risk level, i.e. hand slashed and fingers cut by machine. Three types of risk control activities are determined to minimize the risk, i.e. administration and engineering control and personal protective equipment.