Insurers: Data Science doesn’t need to be so complicated

There has been quite a bit of activity – if not outright hype – regarding the promise of big data and data science. In October, I had a chance to participate in a panel discussion on the promises and perils of data science, in which fellow panelist and digital thought leader Dion Hinchliffe predicted the eventual emergence of “data science as a service.” The time is coming when analytics and accompanying insights would be available online, without the need to hire a roomful of PhDs to help make sense of things.

This has interesting implications for the insurance industry. Along these lines, I recently heard from Mike de Waal, president and founder of Global IQX, who sees data science as one of the most important developments yet for the industry – particularly an industry that increasingly is looking to data to better serve policyholders in new and innovative ways. Consider the many areas where data is playing a role these days: “telemetry, IoT, wearables, AI, chatbots and drones are tools that help group insurers better engage with customers and improve business processes,” according to de Waal. “There is one thing that all of these technologies have in common: data – personal data, to be precise.”

De Waal provides some practical advice to insurers looking to build their mastery in big data:

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Don’t be intimidated. The key is not to feel overwhelmed by the bigness of big data. While the concept of data science may seem bewildering, it actually is based on a basic six-step process that de Waal describes:

1. Frame the problem
2. Collect raw data

3. Process the data
4. Explore the data
5. Perform in-depth analysis
6. Communicate the results

The 80-20 rule applies. Like many things in life, data science is an 80-20 proposition, with “only about 20% of the skills needed will contribute to 80% of the outcomes,” de Waal explains. By focusing on the core 20% necessary to achieve the results you’re looking for “will help simplify the process and keep IT departments focused on the goals you originally set out to achieve with the data.”

Stay laser focused on the business problem to be addressed. “They don’t call it big data for nothing,” de Waal says. “The amount is gigantic. New variables and trends that arise can easily lead you astray from the original question you set out to answer. Stay on track and focus on what you set out to determine. You can always circle around to address new insights later.”

Remember every company is different, and results will vary widely. “Applications for big data in insurance currently center on providing solutions to tasks like setting premiums, fraud reduction and target marketing,” de Waal points out. “How this looks will differ across projects, but regardless of the application, data experts will collect data from various sources, analyze it, and use it to draw conclusions about how the company can improve the bottom line and provide value to customers.”

Actively manage and mitigate risks. “Consumers know that sharing data comes with risks,” says de Waal. “Even the most hardened networks can be vulnerable to cyber-attacks and data breaches, leaving consumers understandably wary of how and with whom they share their personal information. Carriers that take the proper cybersecurity measures will be better prepared to ward off or respond to breaches. Obtaining accreditations such as ISO 27001 may help identify any gaps before hackers do.”

Keep privacy front and center. Privacy is another important factor when obtaining and storing customer data, and needs to be a key consideration every time data is moved. “Consumers want to know what their data is being used for and be assured that it will not be used for anything else,” de Waal points out. “If carriers can guarantee this, studies show that customers are willing to provide personal data in exchange for lower fees and improved services.” In addition, the ability to maintain data privacy and security builds trust – a vital asset in the insurance business. “If trust is established, the possibilities are endless for the kind of engagement and relationships that can be developed and sustained,” he states.

Insurers have already come a long way with their ability to manage and make the most from data, de Waal says. It’s time to take the next step. “The ability to automate business front-ends and back offices has in many cases catapulted insurers into the digital age, and most are landing on their feet,” he states. “This is due in no small part to strong leadership from CIOs, a shared understanding of what customers now expect, and a mandate to provide it. Insurers that master big data will likely leap to the front of the pack. Those that see it as a mystery may quickly find themselves out of the race.”

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Data science Data management Artificial intelligence Drones Insurance technology Customer data Analytics
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