Data-Driven Insurance: A Model for Better Decision-Making
A whitepaper featuring insights from Data Executives at CNA Financial, American Modern, CSAA & Clearwater Analytics
Produced in partnership with:
Amid an unpredictable risk landscape, the insurance industry is on high alert, and its AI, data, and analytics experts have been called to the strategic front line. Facing an onslaught of macroeconomic and geopolitical upheaval, their mandate is a complex one. Crucially, they must advance the industry’s modernization drive by harnessing data for pricing accuracy and operational efficiency, streamlined claims management, and enhanced customer experiences.
While some are rising to the challenge, others are struggling to keep up. By automating mundane processes, critical thinkers can prepare for the next level of decision-making. That’s why we spoke to 4 leading data professionals to find out how they are making data insight the backbone of their organization and opening new doors to success, through data-driven decision making.
Featuring perspectives from industry thought-leaders:
You’ll receive an in-depth report that explores key considerations to best leveraging data in your organization, including:
- 11 key strategies for effective change management and improving data literacy
- Maximizing the fundamental first step to curated insights: data accessibility
- Lessons from Amazon’s Virtuous Cycle on how to remove friction from CX with data-driven decisions
- Tips on clearing the pathway for regulatory rigor and critical thinking
Key insights to look out for:
“Bipin Chadha, VP of Data Science at CSAA Insurance Group is clear that if you are going to make intelligent decisions you have to understand causality. “Correlation is not enough, and most of the techniques we use today are correlation based,” says the data scientist behind numerous patents. Among them: a simulation based virtual advisor that uses conversational AI to help customers make good financial decisions; and a real-time avatar harnessing 360-degree customer data to deliver personalized service and recommendations.”
“Real-time data points for predictive models are already showing what is possible. As David Tian-Ying He, VP Data & AI at CNA Financial explains, “CNA is working to expand its use of predictive models to triage claim complexity to get the right claim to the right claim professional.”
“At a more fundamental level, Clearwater Analytics’ Director of Solutions Consulting, Josh Petersen sees, “manual data entry going the way of the dodo; gone in the next 15 years.” With advanced automation techniques, inconsistency in file formats is becoming a thing of the past. “We are now at a point where we can scrape all of the transaction information out of a PDF, and automatically plug it into our system,” says Petersen. The automation of data management, and enterprise data management will, he believes, continue to shift human resources towards analysis, interpretation, and critical thinking which “remains essential in today’s dynamic environment.”
I hope you enjoy the insights!
Kind regards,
Lucy
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