Insurtech: An opportunity for insurers to start fresh with data

The hype around data in insurance is well-justified – in fact, what industry is more data-driven in its decision making? Most insurers have reams of data but face significant challenges trying to operationalize it. As such, they have big decisions to make about how best to move forward.

Given the volume and value of legacy data, it’s rational to think ‘Job One’ should be putting it to use, unlocking the benefits of more than 50 years of actuarial, policy, claims, and fraud data to inform future underwriting, pricing, processing, product development, and fraud protection. In a perfect world, one with virtually unlimited time and resources for data mining, migration, storage, warehousing, and analytics, that approach would work.

But that’s not the world we live in. Insurance companies don’t have unlimited resources spend wresting value from legacy data to work only to lose out an even bigger, more urgent, opportunity – the one in front of them.

With the sale of new policies continuing to trend down and the "Amazonification" of everything – i.e., customer expectations for instant, elegant online gratification – revving up, the pressure to understand and use data to optimize customer acquisition, deliver personalized experiences, and streamline the buying process is coming from every corner.

Don’t Look Back
A report from Morgan Stanley and the Boston Consulting Group cited a lack of efficiency as a major challenge for the industry, noting that “sales processes remain ‘old-school,’ cumbersome and inconsistent with the fast-evolving customer expectations that are now being set by digital leaders.” Legacy data isn’t going anywhere, but competitive advantage is.

For this reason alone, insurers would be much better served to adopt a data-forward mindset, looking ahead instead of looking back. And the best way to do that is also the simplest: start fresh.

By starting fresh with clean data sets and modern technology, insurers will not only get out of the legacy data quagmire but also set themselves up to take advantage of more cutting-edge technologies such as AI and machine learning. Moreover, consumers are already interacting with your business online. Understanding what they are looking for and what they need by upping your data game now is critical to attracting and converting potential customers, as well as designing and delivering better products.

Laying the Foundation
Quality data and the ability to query and consume it are critical for success in the 2020s. The fastest way to get there is by delivering digital experiences and building clean datasets from scratch with modern technology. This begs two questions: First, what digital experiences generate the most valuable data; and should you build or buy the technology required.

Behavioral data such as who is visiting your site, where they came from, and what they are looking for is invaluable no matter your business model. Insights from these interactions will inform decisions that ultimately make it easier for potential customers and advisors to do business with you.

Depending on your business needs, you might get more value from other types of data. For instance, claims and policy data can be used by actuaries and underwriters to find commonalities and improve products, pricing, and fraud prevention. Accurately pricing policies have a direct impact on profit, so combining data (internal and external) with predictive analysis tools can enable insurers to adapt quickly to market demand and identify potential fraud.

In fact, Boston Consulting Group noted that insurers who fail to adapt to new pricing models and technology disruptors in pricing will “lose competitive edge to rivals that better understand what is driving their clients’ needs and willingness to pay.”

In the future, on-demand policy creation based on fresh data has the potential to unlock underserved or underinsured consumers, unlocking new revenue streams while reducing customer acquisition costs.

Build or Buy?
Conducting a thorough build vs. buy analysis can help insurers compare the costs, benefits, and timing of in-house, data-centric solution development vs. partnering with a vendor, but there are other intangibles that can be harder to quantify, such as missed-opportunity cost and user experience that should also be considered. This is especially true in an era where digital-native disruptors are pursuing the same prospects as insurance incumbents. Yet for many companies, the decision simply comes down to a single question: do I have (or can I hire) the IT staff, data scientists, and user experience experts required to do this in house?

Today, with all the possibilities of a new decade in front of us, the answer for most insurers is no. Partnering with an insurtech is is typically much faster, less risky, and more successful than going it alone. In addition, partners provide the modern infrastructure, ongoing innovation, regular updates, and access to high-skilled talent that help you keep your focus on what you do best: selling policies and serving customers.

Existing data isn’t going anywhere – and it still has value – but starting fresh is the right solution in the near term. Legacy platforms can be modernized and data sets migrated behind the scenes while new data is generated and put to work now. Over time, the ability to merge data sources, including that of third-parties, and the super-enriched datasets that will result, will unlock even more business opportunities. Data has always been the bedrock of the insurance industry, but starting now by starting fresh will ensure its future.

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