Proposal and reporting of additional identification of clients in the insurance company

The thesis primarily deals with the issue of client identification in the insurance industry. The main objective is to design and implement a reporting solution that will enable effective management and monitoring of unidentified clients, including the problems associated with this process. The reporting solution consists of several phases, including analysis of existing data in the data warehouse, subsequent processing and transformation of the data into a format suitable for a Business Intelligence data model and final upload of the data into the Microsoft Power BI visualization tool, where the report itself is created. The solution also includes a pilot and test design of the process, which could potentially be used in the form of an application as an option to additionally scan the existing set of clients and possibly identify an unidentified client based on similarities using different methods and approaches. Following the tested methods, an overall evaluation of the results in terms of their accuracy and practical application in the context of this issue is performed. The overall solution provides a basic framework through which an insurance company can effectively improve the client identification process, minimize errors caused by incomplete or inconsistent data, and optimize customer service. The results of the work also highlight the potential use of advanced mathematical methods, including machine learning, to further develop and streamline processes in a traditional company.