Why data will define value for insurers - and how to harness

its full potential for success

Data has always been at the core of the insurance industry, forming the bedrock of actuarial science and risk assessment. In today’s hyper-connected world, insurers have access to vast troves of organized (traditional) and unorganized (non-traditional) data. New customer expectations demand that insurers differentiate their product and service offerings to the extent that they feel tailor-made for the customer’s specific needs. Leveraging data to deliver on those expectations is one of the best opportunities insurers have to delight their customers and stand out from the competition.

Traditional insurers (incumbents) face a rising threat from competitors who have already mastered data-driven personalization. In addition to being more nimble, InsureTech players are able to package better value per dollar of premium. To compete, incumbents must build their capabilities and infrastructure so they can harness data for insights into their customers’ needs and respond with products and services that meet them.

Personalization: The key to customer-centricity

The best source of competitive edge in the ever-evolving market is to personalize every step of the customer journey, from generating quotes to processing claims. While personalization is not new, access to new data sources provides an opportunity to take it much further. Through convenient, automated channels, insurers can communicate with customers at optimal times, providing pertinent information in preferred formats. A more consumer-centric approach delivers value, improves customer satisfaction, and boosts engagement, which, in turn, reduces abandonment and increases retention.

Reluctance to pursue this path is often due to privacy concerns. Fortunately, although consumers have privacy concerns, most are happy to share more personal information if they receive better, more relevant services in return. One study in the UK, for example, found 59% of consumers were willing to share more personal data if this helped insurers align pricing more directly with individual levels of risk.

Maximizing customer value through data-driven insights

Examples of the new data sources available to insurers include: 

• Wearable devices collecting data about health and physical activity.

• Cell phone apps or vehicle telemetry to monitor driver behavior.

• Smart home devices e.g., smoke detectors, security cameras and thermostats providing information on home conditions.

• Drone and satellite high-precision aerial imagery to assess wildfire hazards.

• Social media and public records to gain a more nuanced understanding of individual and business risks.

All these data sources can be leveraged to enhance risk assessment, drive proactive risk management, boost fraud prevention and improve underwriting effectiveness. They can also underpin new pricing models that reflect knowledge of the customer and reward lower risk- or positive behavior. For example, in auto insurance, usage-based, traffic-based, or timing-based models are already in use.

What’s more, predictive analytics make it possible to drive marketing campaigns and offers that align with customer needs even before they arise.

Overcoming the data conundrum

So why are many incumbent insurers still struggling to fully leverage this wealth of data opportunities? 

While insurers already have a massive amount of historical and traditional data, quantity doesn’t always equate to quality. Legacy systems often leave data siloed, unreliable or inaccessible, sometimes a combination of all three. Insurers may rely on a growing number of third-party providers for additional datasets, but still fall behind new InsureTech players who don’t have the legacy challenge. These constraints make it almost impossible to create a holistic, fully informed view of the customer, leading to lost opportunities. 

Insurers also face a more complex compliance landscape as governments widen the net of data-protection regulations. It’s no surprise that in one industry study by State Street, 62% of insurers reported channeling a significant amount of resources to manual data management, and nearly three-quarters cited improving data management processes as a key driver of competitive advantage. Only flexible, adaptive strategies will enable insurers to keep pace with this fast-moving data landscape, and avoid financial and reputational risks.

Thoughtworks: Your partner in data-driven transformation  

At Thoughtworks, we have established practices and a long track record of developing data strategies and platforms that make legacy systems and interfaces fit for purpose in a more customer-centric environment. We counsel organizations to avoid a ‘big bang’ approach to modernization that aims to overhaul infrastructure all at once, prioritizing instead tackling multi-generational tech debt issues in a safe and incremental way.

The opportunities for personalization and the need for compliance support the case for a democratized, decentralized, value-oriented architecture that positions insurers to make the most of all their data resources. The end goal is to make data quickly available across a business for multiple uses, overcoming the segmentation and limitations often associated with legacy systems. 

In this “data as products” approach, data is broken down into distinct ”products”, which are controlled by teams aligned to domains, such as policy, claim or customer.  Each team focuses on a set of customers that consume the data products they manage and works to optimize the value they provide. This changes what gets prioritized and results in better insights, paving the way for smarter decisions and greater customer value. 

We also help insurers unlock existing data assets by modernizing inflexible interfaces with our engineering best practices, evolutionary architecture, and domain-driven design, reducing friction in ingesting new data sources and interchanges with third-party providers. 

When organizations embark on the personalization journey which is data driven, they have to keep in mind;

1. development is incremental (strangulated) with evolutionary architecture
2. founded in robust data governance which can quickly adapt to the changing data and privacy regulations and 
3. the data breakdown approach is domain-product centric with domain-driven design

These approaches enable incumbent insurers to reinvent their infrastructure in a way that ensures they excel in the race with InsurTech disruptors. To thrive, incumbents will need to not only manage data better, but to use that data as a basis for insights and innovations that enhance customer experience and customer value, creating an enduring advantage in the marketplace.

For further perspectives on how we went about creating the Data Mesh Platform for one of the banks in Europe you can look at our ING client story.  You can learn about our approach toward building an evolutionary data platform with the Bosch client story. A view on how to manage data better through data governance frameworks in financial services is provided in this article.