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Data & Analytics

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Big Data: Quality Over Quantity

The majority of C-level executives agree that they could better leverage data, but they don't necessarily need more of it.

The global volume of data is growing by the millisecond. Every minute, 98,000 tweets appear in feeds around the world and add to its vast amount of data -- 90 percent of which was created in the last two years.  

In a survey of C-level insurance executives on their use of big data, KPMG determined that nearly 70 percent consider data and analytics of critical importance to revenue growth, said Garrett Flynn, managing director, at this year’s KPMG Insurance Conference held in New York. The research also indicated that insurers could improve their use of big data and analytics but lack the data quality or appropriate structure to do so.

Many organizations do not fully understand the meaning behind big data, said Flynn. Plenty of businesses believe that big data is solely about massive data volume, but it is actually defined by its volume, velocity, variety, and validity. Its volume is constantly expanding, its velocity and variety are increasing, but its validity continues to wane.

Another common misconception about big data is that it is a siloed organizational responsibility. “Data is not just an IT issue. It’s not just a business issue. It’s an organizational issue.” He also debunked the idea that more information leads to greater insights. “More is not necessarily better,” he said, when it comes to big data.

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Flynn also addressed false perceptions concerning analytics, which businesses use to derive maximum value from their data. Analytics is not a responsibility left to data scientists, as many organizations believe, nor is it entirely about software and tools. The true meaning behind analytics involves enabling employees across the organization to formulate better questions and improve their decisions through valuable insight. 

Despite its popularity, there are many who believe that analytics is just another business trend -- a dangerous perception, Flynn said. “It’s table stakes. If you’re not doing analytics, you’re going to get left behind.”

Insurers’ analytics adoption is on the uptick; for example, 80 percent of insurers are using predictive analytics for personal auto. However, there remains room for growth. Half of consumers would use UBI to receive discounts on their premiums, Flynn said, but UBI devices are installed in less than 1 percent of American vehicles.

Flynn suggested that insurers use their available data to prevent claims through proactive property monitoring, improved risk profiles, and better consumer segmentation, all of which can contribute to growth, cost optimization, and customer retention. Big data also enables insurers to access new channels, capabilities, and methods of presentation.

For those still organizing their big-data approaches, he suggested developing a strategy that will deliver value every three months. This timeframe allows insurers to prepare for technological or business change. 

Kelly Sheridan is the Staff Editor at Dark Reading, where she focuses on cybersecurity news and analysis. She is a business technology journalist who previously reported for InformationWeek, where she covered Microsoft, and Insurance & Technology, where she covered financial ... View Full Bio

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