Two-thirds of insurers find data quality lacking, hampering analytics

Poor data quality is the biggest challenge for insurers looking to implement advanced big data and analytics in their enterprises, according to West Monroe Partners’ study, “Data Driven Insurance: Harness Disruption and Lead the Way.”

Two-thirds of the 122 respondents to the 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.

West Monroe suggests that insurers measure data quality issues through an integrated exception reporting process, documenting issues that demand attention, and ideally managed by a data governance committee.

“The problems must be identified and addressed before they go downstream for analysis,” the study says.

Overall, 57% of insurers surveyed say they somewhat or strongly agree that their companies are fully realizing the benefits of advanced analytics. The most commonly cited benefit was customer experience (27%) followed be reduced claims costs (21%) and increased sales (14%).

“Many of these areas are interrelated – e.g., improved product development was likely viewed by some respondents as a way to increase sales or improve customer experience,” the study says.

Overall, West Monroe recommends, “insurance companies should use advanced analytics to focus on manageable tasks with goals like increased engagement, improved production by existing advisors and reduced attrition.”

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