Analýza pojistných podvodů v České republice a jejich prevence

Abstract

This thesis deals with the analysis of insurance fraud in the Czech Republic and its prevention. The aim of the thesis is to identify the most common types of insurance fraud, the main causes and impacts, to evaluate the current methods of detection and prevention and to propose measures to increase the effectiveness of the fight against this problem. The theoretical part of the thesis focuses on the definition of insurance fraud, its legal framework in the Czech environment, typology of insurance fraud and perpetrators. It also describes traditional and modern methods of insurance fraud detection, including the use of machine learning and artificial intelligence, their effectiveness and trends. The practical part includes an analysis of insurance fraud in the Czech Republic in the period 2019-2023 based on available statistics and case studies of real insurance fraud in the Czech Republic, which illustrate different approaches to detecting and solving it. The results of the work show that modern technologies such as big data analytics, machine learning and AI are playing an increasingly important role in identifying insurance fraud. At the same time, it is clear that effective prevention requires a combination of both legislative measures and technological tools, as well as education among insurers and the schema_dspacedb.