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Is Analytics the Future of the Insurance Industry?

by Precise Leads

October 2, 2017

Insurers have begun to harness the power of analytics. But could they be doing more?

The insurance industry is built on an enormous foundation of data. For decades, that information streamed into actuarial tables based on previous claims and demographic statistics. Underwriters then used those archival numbers to predict future loss costs and set rates.

Insurers now possess new tools to analyze data, thanks mostly to artificial intelligence. Instead of relying on historical knowledge, insurers and underwriters can crunch real-time data to predict potential risks and possibly prevent losses. While the industry has made great strides in the use of data analytics, it has yet to unleash its full power, at least according to one survey.

A recent report from West Monroe Partners, a technology consulting firm, found that only 11% of more than 200 property and casualty and life insurance executives “strongly agreed” their organizations were using advanced analytics to its fullest potential. Only 46% agreed “somewhat” with that statement. “Overall, insurance companies have work to do to position advanced analytics most effectively within their organizations and to fund it adequately to realize the benefits it can produce,” the report’s authors wrote on PropertyCasualty360.com.

Data Analytics Now — and in the Future

In a PropertyCasualty360.com article, Mark Breading, a partner at advisory firm Strategy Meets Action, details five areas where data analytics has — or can have — the most impact within in the insurance industry. So far, the industry has excelled in using data analytics to describe and diagnose what occurred and the cause of the event. Likewise, insurers have increased their predictive analytics capabilities.

Breading describes two emerging data analytics frontiers: discover, or the ability to uncover new risks and therefore, new opportunities; and prescribe, which enables insurers to intervene and impose actions to prevent a loss. Regarding the latter, he offers connected cars as an example of how insurers can use prescriptive data analysis.

Currently, telematics collect what Breading terms “static” data about the vehicle, such as the model, driver, and usage information. By pairing that information with real-time geospatial data such as vehicle location and road conditions, insurers can immediately respond to accidents. Alternatively, insurers could employ telematics and geospatial technology to lead drivers to safer routes.

In addition, insurers have compiled enough historical data to assess the cost of property damages due to storms. To lessen those costs, however, insurers can now use real-time geographic and weather data to alert policyholders to protect their properties.

Better Customer Service

Improved customer service was rated as the number one benefit of data analytics by nearly 30% of the executives polled by West Monroe Partners. Brokers, in particular, cited enhanced customer experience through data analytics as a way to differentiate themselves in an increasingly commoditized product market. Other potential benefits from data analytics include reduced claim costs and increased sales.

Hugh Owen, Senior Vice President of product marketing for data intelligence software company MicroStrategy, Inc., underscores those points on ItProPortal.com. A deep dive into customer data, he writes, uncovers insights in their behaviors and preferences, which, in turn, enables insurers to offers policyholders individualized products and services. Owen also predicts better underwriting processes, quicker claim settlements, and easier access to client and prospect information by sales and distribution teams through data analytics.

According to the West Monroe Partners survey, insurers have already begun to make inroads in those areas. More than half said they employ advanced analytics for claims modeling and reduction; 42% use analytics for actuarial model testing, and 35% have integrated it into prescriptive marketing and sales functions.

Challenges Ahead

Along with the potential benefits, data analytics brings challenges, as well; 64% of the respondents in the West Monroe Partners poll claimed that ensuring data quality and accuracy are the most significant among these issues. Similarly, more than half pointed to inaccurate data as the top risk.

Other challenges include integrating data across separate claims and policy systems, data security, and other privacy concerns. Moreover, P&C insurers in the West Monroe Partners report mentioned “analysis paralysis” as a possible hurdle of scrutinizing huge amounts of data.

“It’s one thing to collect and interpret as much data as you can get your hands on, but to do it in a way that makes a difference to your business goals is the challenge,” Willem van der Hooft, Business Development director at Van Ameyde, a European-based claims management solution firm, told Raconteur. Yet it’s a challenge insurers must tackle to remain competitive in the future.

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