Data Lakes for Insurance Industry: Exploring Challenges and Opportunities for Customer Behaviour Analytics, Risk Assessment, and Industry Adoption

Bálint Molnár, Galena Pisoni, Ádám Tarcsi


The proliferation of the big data movement has led to volumes of data. The data explosion has surpassed enterprises’ ability to consume the various data types that may exist. This paper discusses the opportunities and challenges associated with implementing data lakes, a potential strategy for leveraging data as a strategic asset for enterprise decision-making. The paper analyzes an information ecosystem of an Insurance Company environment. There are two types of data sources, information systems based on a transactional databases for recording claims, as the basis of financial administration and systems policies. There exists neither Data Warehouse solutions nor any other data collection solutions dedicated to utilizing by Data Science methods and tools. The emerging technologies provide opportunities for synergy between the traditional Data Warehouse and the most recent Data Lake approaches. Therefore, it seems feasible and reasonable to integrate these two architecture approaches to support data analytics on several aspects of insurance, financial activities, risk analysis, prediction and forecasting.


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