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Big Data

Insurance Technology

Big Data Report, Insurance Technology Report

Big Data in Insurance - Thematic Research

Insurance companies need “better” data security or “more” data security

Insurance is a highly data-intensive industry, making it extremely important for insurers to manage large volumes of data from both traditional and non-traditional sources. As a result, many insurers are spending significant amounts on building Big Data capabilities, finding that Big Data analytics can have an impact on nearly all insurance processes, from product development to claims management.

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  • What you need to know...
  • Simplification, cost reduction and revenue growth are the three key drivers behind Big Data’s adoption in the insurance industry.
  • By 2016 it is estimated that 25% of global insurers use Big Data analytics to detect fraud cases, according to a survey by Deloitte.
  • There is high demand for contributory data and innovative modeling, supported by a “forward and backward looking” approach that blends actuarial models, science advancements, financial demographics, and government data.
  • Property insurance is arguably the area with the most potential to use Big Data, but the price of equipment means it is currently restricted to the top end of the market.
  • Motor insurance has already been influenced by Big Data. Telematics and driver analysis technology are not yet mainstream, but they are increasing in popularity.

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Using Big Data to design new insurance products

Big Data analytics is enabling insurers to shift towards customer-centricity by analyzing preferences, behaviors, and attitudes. Score-based models can help insurers design customized products, using demographics, driving and health records, and credit information.

GlobalData’s Big Data in Insurance report analyses how insurers are spending significant amounts on building their big data capabilities, finding that big data analytics can have an impact on nearly all insurance processes, from product development to claims management.

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