Χρήση μεγάλων δεδομένων στις πωλήσεις και το marketing των ασφαλίσεων υγείας
View/
Keywords
Μεγάλα δεδομένα ; Ασφαλίσεις υγείας ; Αλγόριθμοι μηχανικής μάθησης ; Επεξεργασία δεδομένων σε πραγματικό χρόνο ; Εξατομίκευση προϊόντων ; Πρόβλεψη αναγκών πελατών ; Τεχνολογίες cloud ; Αποθήκες δεδομένων ; Ιδιωτικότητα ; Ρυθμιστικά ζητήματα ; Προκλήσεις μεγάλων δεδομένωνAbstract
This study explores the use of Big Data in sales and marketing within the health insurance sector, highlighting their prospects, challenges, and strategic significance in the industry. Beginning with the concept and characteristics of Big Data, the research provides a historical overview, analyzing technological advancements and data management techniques. Special emphasis is placed on the application of Big Data in the insurance sector, including the collection and analysis of data from electronic health records, wearable devices, and social networks. The study examines how insurance companies leverage machine learning algorithms and real-time data processing technologies to achieve effective customer targeting, accurate needs prediction, and product personalization. Additionally, it investigates the role of tools such as data warehouses and cloud technologies in enhancing organizational flexibility and sustainability. The study also addresses challenges related to data privacy, the ethical use of artificial intelligence, and protection against cyberattacks. Specific studies, such as those by Gartner (2021) and McKinsey (2018), demonstrate that leveraging Big Data increases revenue and reduces operating costs, thus strengthening the sustainability of the sector. Finally, the role of actuaries is highlighted, as their use of statistical models and predictive algorithms contributes significantly to risk management and strategic development within the insurance industry. The study concludes that Big Data, combined with the expertise of actuaries, serves as a critical driver for digital transformation and innovation in health insurance.