Data Quality Hindering Insurers, Study Finds

Poor data quality is the greatest challenge for insurers looking to use advanced big data and analytics in their business, according to a study called “Data Driven Insurance: Harness Disruption and Lead the Way.”

Two-thirds of the 122 respondents to the West Monroe Partners’ survey said data quality and accuracy was the greatest challenge to advanced analytics. And, 51% said that the greatest risk was inaccurate data.

“It’s obviously difficult, if not impossible, for organizations to derive much value from bad data – and there’s the matter of convincing individuals throughout organizations that the data is accurate and will stay accurate,” the study says.


Key takeaways from the report:

  • Data’s opportunity as a business accelerator: About a quarter (27 percent) of respondents named improved customer experience as the greatest benefit of advanced analytics, a summary said. Twenty-one percent said they could reduce claims costs and 14 percent chose increased sales.
  • Major worries about data quality: Nearly two-thirds of respondents said data quality and accuracy was the greatest challenge associated with advanced analytics. About half said inaccurate data was the greatest risk.
  • Current focus on claims modeling and reduction: Fifty-one percent of respondents said they already used advanced analytics in that area; 42 percent said they used actuarial model testing.
  • Lack of investment in disruptive data sources: Seventy-six percent of respondents said they were not investing in disruptive data sources, though about half of those respondents said they were considering making an investment in secondary sources that would augment their own data.


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