Despite its rising popularity, the novelty and merits of big data risk analysis are still debated. This perspective article contributes to the debate by clarifying what constitutes big data in the context of risk analysis and proposing that the discussions of big data attributes (i.e., scale, speed, and structure) and big data methods should go hand in hand. Simple examples are used to illustrate the differences between big data risk analysis and traditional approaches. Finally, a distinction is made between the conceptual definition of risk and how risk is measured to clarify the contributions of big data to risk assessment, and to highlight the importance of explicitly accounting for strength of knowledge in conducting big data risk analysis.
Keywords: Big data risk analysis; predictive risk analytics; risk science.
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