Data plays a crucial role in risk analysis and insurance studies by providing insights into human activities and natural phenomena. Insurance data is collected from various sources, including industry reports, official data, surveys, and media outlets. To ensure the accuracy and reliability of the data, it is common to preprocess it by identifying missing and erroneous values, categorizing data, and other techniques. However, the quality of data is also influenced by the methodology of data collection. The method of data collection can significantly impact data quality. While digital technologies have made data management easier, they also introduce new challenges that must be addressed. This article explores the impact of data collection methodologies on data quality and discusses the limitations and drawbacks of digital technologies in data management.
