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Analysis: Bad data - A risky business for insurers?

Data overload

Data is everywhere: good data, partial data, valuable data, bad data. Insurers need data to measure and price risks but do they take enough care in assessing the quality and provenance of the data they are using and are their processes sufficiently robust?

The tools that are now available to consume, manage and interpret massive datasets are so powerful that there is growing concern insurers could be feeding in data that contains underlying weaknesses

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