Scouting through the data jungle: Data analytics in the insurance industry

Scouting through the data jungle: Data analytics in the insurance industry

A large volume of collated information alone does not guarantee deeper insights. To gain these and use raw data economically, complex analytical methods and intelligent processing are required.

“Examples of artificial intelligence (AI) can be found in various areas of the insurance industry today – for example in underwriting and claims”, says Wolfgang Hauner, Chief Data Officer at Munich Re. “AI can support consultants in their work, helping with fact-checking and recommending courses of action, for instance.” By contrast, processes in underwriting are becoming smarter: “All the available data and sources are called upon here, improving processes and the customer experience.”

Things are also getting smarter in claims. “Reaction times are getting shorter and insurers can more glean more information – which in turn leads to efficiency gains and better decisions.” Big data and analytics allow the efficient processing of losses with low volumes and high demand rates. Thanks to innovative data technologies, insurance can also be offered that was previously considered unprofitable or difficult to assess in terms of its risk.

In concrete terms, that could mean more attractive covers for certain types of diabetes or performance guarantees for wind farms. Furthermore, processes and information can be amalgamated in order to transfer some underwriting elements to automated risk management platforms. With the aid of AI workflows, it is also possible to develop applications which enable the early recognition of losses the identification of potential cases of insurance fraud. Munich Re has developed a broad range of prototypes and products which are being tested or are already in use. To learn more about them, have a look into our online magazine.

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