Big Data and Decision-Making in Insurance Organizations

Insurance, manifested in countless forms like health or liability insurance, is a key component of risk management in modern society. In recent years, big data analytics and data-driven algorithms have increasingly influenced the work of insurers and its impact on people’s lives. Car insurers often use big data analytics to monitor and analyze the driving behavior and performance of policyholders and adjust their rates accordingly.

Yet although these changes have significant social implications, we know surprisingly little about how digitalization is affecting the organizational processes of insurance companies. We believe that an inquiry into the effects of digitalization on insurers as organizations can hold important insights, as it may also contribute to our understanding of how their processes affect society.

Drawing on an extensive review of existing research and a content analysis of insurance documents, we highlight the following three aspects: First, we see the use of big data as the result of a sensemaking process that has brought a new species of knowledge production into the preparation of decisions. We stress that although new techniques such as data-driven algorithms promise increased analytical precision, they still remain socially constructed interpretations. Second, numbers are excellent “persuaders” because they suggest rationality and objectivity, with the end effect of creating legitimacy. Therefore, big data-based decision-making promises a new dimension of credibility that enables insurers to make a fundamental switch: from solidarity-based policies to insurance based on the principle of individual accountability. Third, the power of digital computing makes it possible for decision makers to be replaced by algorithms. This raises the question of whether automated decisions can actually still be considered decisions and to what extent decision-making, the core element of organizations, is in the grips of transformation.