Data quality and data governance in insurance corporations

This paper will focus on the topics of data governance and data quality in the insurance industry. Nowadays, in fact, more and more companies are choosing to invest in order to have a solid data analysis and management structure, in order to ensure better customer service, cut costs, and have more robust information available to prepare financial statements. In addition, within the paper, an attempt will be made to bring out the idea that data governance and data quality are closely related, and investment in one area implies an eye for the other; consequently, although they are distinct, they are "two sides of the same coin." Since the information processed and managed by these companies has a purely financial nature, the first part of the paper will be an overview of the general principles of insurance financial reporting and international accounting standards; in particular, there will be a special focus on IFRS9 and IFRS17, as they are more closely related to the insurance context and are of particular interest to the project covered during the internship period. The following parts of the thesis will focus on data governance and data quality in general, using scientific literature as a source to provide benefits, costs, challenges and key aspects. Finally, this information will be useful for a better understanding of the last chapter, which focuses particularly on the work I did during my curricular internship at EY, concerning a project for a client operating in the insurance and asset management sector. The information provided in this section will not be extremely detailed (due to confidentiality constraints on sensitive data and the identity of the customer) but it will still be enough to relate what was described in the previous part and to understand why insurance companies need to have a solid data governance structure linked to a solid data quality policy.