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How data analytics will change the risk and insurance industry—and your career

Big data is changing everything.

That’s hardly a bold claim these days. Consulting firms, thought leaders, whitepaper authors and journalists are all predicting the significant impact data analytics will have on industries ranging from finance to health care. Enterprises and business leaders in these industries are investing considerable time and effort into preparing for the data science revolution that’s already well underway.

The insurance industry is not immune to this rising trend, and big data has indeed already led to some substantial changes in how insurers operate. However, many of the fundamental concepts behind data analytics have driven the insurance industry for decades. Utilizing customer data, risk analysis techniques, to set pricing is nothing new for insurance professionals. That data-driven decision making is the backbone of how insurance works.

But even in the insurance industry, where data has always been a core business driver, the sheer volume of data and how it’s being analyzed and put to use have created a seismic shift in how the industry works. Big data—and the field of data analytics—is exploding beyond traditional risk selection and underwriting practices into virtually every aspect of insurers’ operations.

Only organizations that prioritize integrating this new approach to data and individuals who successfully adopt a data mindset will effectively harness this new reality in the insurance industry.

Big data is truly changing everything.

An Overwhelming Fraction

In the last two years, humans have created more data than in the previous history of the entire human race. For insurers, this influx of data comes from a host of emerging sources, including telematics, online and social media activity, voice analysis and wearable devices, to name a few. Up until now, the massive quantities of data have proven to be a little overwhelming. Insurance companies process only 10 to 15 percent of the data they can access. And most of the data that is analyzed is structured, meaning it’s organized and usually housed in databases that can be linked to each other and cross-referenced.

Unstructured data, on the other hand, is a lot more unwieldy and often requires advanced data science techniques to analyze it and to use it to make business decisions. But unstructured data is also where many of the industry-changing insights lie. That’s why emerging data analytics technologies centered on artificial intelligence and machine learning are focusing on giving this unstructured data an order and purpose to drive business decisions. These new analytic approaches apply to relatively new sources of information, like programs that scan customer calls for keywords, as well as traditional sources of data, like systems that automatically categorize adjusters’ notes.

Insurers are working quickly to capitalize on these new sources of data and put them to good use in entirely new areas of business operations. Currently, 42 percent of insurance carriers use big data techniques in their pricing, underwriting and risk selection processes. In two years, that number will jump to 77 percent, according to a 2016 Towers Watson report.

Similar leaps in big data use are expected in loss control and claims management, understanding customer needs and product development. But the impact data will have is projected to go beyond products, pricing and customers. The use of big data in making better management decisions and improving marketing efforts is expected to triple in the next two years, according to the same report.

As data science continues to expand and pervade every aspect of insurance organizations’ operations, an understanding of big data principles cannot stop at data scientists and analysts. All employees, from the C-suite and department managers to claims reps and underwriters, must adopt a data mindset and fully embrace this new way of thinking.

Trusted Knowledge for a New Reality

As an established thought leader in the insurance industry and knowledge partner for insurance professionals, The Institutes has closely monitored the growth of data analytics in the industry.

To address an identified vacuum of practical industry knowledge, The Institutes has developed the Associate in Insurance Data Analytics (AIDA™) designation — the first insurance-specific education program on data analytics. The AIDA is more than just a new educational program; it’s the latest milestone in The Institutes’ century-old mission of providing essential knowledge to the property-casualty industry.

Like the CPCU and dozens of other programs and designations from The Institutes, the AIDA empowers individuals and organizations to stay current and knowledgeable on the issues affecting an ever-evolving industry. This designation combines established data principles with cutting-edge information and best practices on big data and its impact on insurers.

The AIDA provides risk managers, underwriters and claims pros a learning course to help them develop a data mindset that will become even more essential to insurance operations in the years to come. Managers, senior executives and data specialists can immerse themselves in the basics of the latest models and techniques used in modern data analytics.

The AIDA offers an overview of data science and allows professionals to drill down into how insurers are using data today, from predictive modeling and data analytics strategies like clustering and classification trees to claims analysis, fraud detection and change management. It’s a solution that provides today’s business leaders with the data acumen to work with data scientists to drive real innovation and change.

Learning That Delivers Results

For as quickly as this new reality is evolving, data science continues to be a developing field with ongoing challenges. Insurers are eager to find better solutions to issues surrounding data security and data quality and to improve efficiency in processing large amounts of data, especially unstructured data.

As insurance organizations compete to solve these big data challenges and implement more effective and robust data analysis systems, new opportunities and challenges are developing all the time. Data scientists at the most forward-thinking organizations are already looking past analyzing data using existing algorithms and instead are using big data to solve clearly defined problems.

The next era of data science will use machine learning to automatically identify meaningful patterns in data and create the algorithms and will define the opportunities for improvement in the first place. The AIDA designation details these emerging best practices, positioning employers and individuals to meet these new opportunities with a data-driven mindset that minimizes the learning curve that comes with new technologies and approaches.

Organizations that can infuse this data mindset into business operations will have a serious competitive advantage over enterprises that don’t catch on as quickly. Individuals who are able to drive improvements in organizational use of data science will have a leg up not only in their current position but in their overall career. With the new AIDA designation from The Institutes, organizations and individuals have access to the necessary knowledge to meet the challenges of the much-hyped changes to the insurance industry head on.

  

To learn more about the Associate in Insurance Data Analytics designation offered by the industry’s most respected knowledge provider, visit The Institutes’ website.

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