The proliferation of big data in the insurance industry has transformed the dynamics of formulating policies that would help businesses prosper. Actuarial calculations are being done by analyzing the data sources--making them more accurate and responsive. Moreover, big data provides reports on weather, transport strategies, the introduction of new technology, and other vital information from countless sensors and tracking bots, which can be leveraged by the insurance industry to investigate claims during a disaster. These data are leveraged by insurance companies to assess the real-time risk associated with the dynamic industrial environment.
Moreover, insurance companies are applying data analytics to decipher the structured and unstructured data updated every second to predict the future, detect negative or positive anomalies as well as trends in the market. Machine learning is being introduced in the insurance landscape to automate the analytics and form an algorithm that will navigate properly through these new sets of data.
Artificial Intelligence, deep learning, neural networking, and machine learning would make data mining easier for insurance industries. These new technologies will transform insurance investigations by implementing a far more agile and accuracy focused system. Additionally, predictive analytics and machine learning can be used to determine customer expectations and drive the individual satisfaction rate to its optimum. Giving in to the growing tide of data, insurance companies have to constantly update and enhance their analytics system to mine data beyond reporting and stay competitive in the market.