Monitoring the Conformity to the Unemployment Insurance Law in Binh Duong province between 2013 and 2015

From the context of Binh Duong province, I choose the issues of unemployment law monitor as the topic of my master thesis. In order words, my topic is “Monitoring the Conformity to the Unemployment Insurance Law in Binh Duong province between 2013 and 2015”. Binh Duong is an emerging province that is a place for FDI companies to choose for their investment. The labor migration to Binh Duong then increases considerably. This situation challenges the unemployment insurance management in this province. The control of managing and implementing the unemployment insurance legislation is not effective. The number of unemployment insurance inspections is low that leads to the violation of unemployment insurance law. The post-inspection and inspection process in some localities has not received serious attention from the government. The ineffective monitoring of post-inspection has hindered the quality and efficiency of inspections. For examining the monitor of unemployment law, the thesis uses both qualitative and quantitative research methods. The thesis firstly collects secondary data on implementation of the unemployment insurance law in enterprises in Binh Duong from 2013 to 2016. Then the thesis uses quantitative to examine the factors that influence the obedience of the enterprise in Binh Duong to unemployment insurance. Thirdly, the thesis uses case study, deep-interview to discover the reasons that cause the law disobedience about unemployment insurance in enterprises in Binh Duong. The sample size is 100. Likert Scale with 5 point is used. For quantitative data, the thesis use SPSS 20.0 to carry out regression analysis to examine the relation between dependent variable (law conformity) and independent variables developed in theoretical framework. Coefficient rate is 95% with p = 0.5%. The process of analyzing data was conducted through 4 phases that are descriptive, reliability, validity and regression analysis. There is the strong relation between IT Application and Law Compliance Monitor. The other three factors (Profession of Public Servants, Labor Union and Relevant State Organizations, The reinforced legal status Social Insurance Organization) also had positive effects on Law Compliance Monitor and these predictors should be used in developing and improving Law Compliance. However, one remaining factor including Volume of Cost did not have impact on Law Compliance Monitor

Guidelines for artificial intelligence-driven enterprise compliance management systems

The use of Artificial Intelligence (AI) to design and drive a Compliance Management System (CMS) at an enterprise level is a strategic decision to be taken by large organizations. Given the complexity this decision entails, conceptual guidelines addressed to senior management and board of directors are required. The original contribution to knowledge and practice of this research lies in the understanding of how compliance management systems are set-up in organizations, by using the CMS framework derived from literature, later confirmed by empirical data. Furthermore, this research originally contributes to both knowledge and practice, through the depiction of the enablers and barriers of AI adoption in organizations, as well as the recommended conceptual guidelines for AI-driven CMSs. Using three case studies as a research method, this paper investigates the current set-up of CMSs, as well as the enablers and barriers of AI adoption and then discusses the driving themes of strategic importance to organizations when sourcing AI aimed at supporting the management of compliance. These themes are: CMS components structures responsibilities, enablers and barriers of AI, control and compliance of AI applications, compliance by design, data governance and data management, cyber security, information technology infrastructure, regulation and regulators, and collaboration with external parties. The thematic findings of this research are additionally discussed in the context of the three lines of defence of an enterprise (business units, support functions, audit functions), making this an organizational framework for the design of an AI-driven CMS. The research concludes with the recommendations that in order to adopt an AI-driven enterprise CMS, organizations should do the following: strategically decide the type of AI organization they want to be, involve stakeholders in the design phase of new policies and AI applications, invest in data governance and IT infrastructure, tap on best practices from cyber security, and collaborate with external parties and regulators