What if the insurance industry could be built around the fundamental principle of prevention rather than cure?
Rory Yates, head of strategy, EMEA, and Asia Pac, EIS, takes a look at how embedded cover can be part of the solution
In essence, insurance was created to help make a really bad day, less bad. By helping to manage risk and reduce the impact of loss, it enables us, our businesses and society as a whole, to recover and take advantage of new opportunities.
But what if insurers could help you avoid loss entirely? That’s part of the promise of Embedded Insurance 2.0., and it’s going mainstream sooner than you think.
Utilising cloud computing, APIs (application programming interfaces), data, and the power of AI and machine learning, experience economy leaders like Amazon and Netflix have radically changed people’s expectations around personalised, context aware customer experiences. Now, with the new generation of cloud-native insurance core systems, those same capabilities are available to insurers and will have a massive impact on their business models, revenue, and customer experience.
One manifestation of this is embedded insurance 1.0, which has offered important opportunities to simplify and expand insurance distribution.
CASE STUDY: POS COVER ON JEWELLERY ITEMS
Here’s a real example. A chain of jewellers in the United States offers automatic coverage against theft or damage on engagement rings for a set period at the point of purchase, giving you time to add it to your home insurance or add another insurance cover.
Seizing opportunities to insure expensive, fragile, and easily stolen or lost items (jewellery, phones, laptops, headphones, gaming, and IoT devices) is all well and good, but we’ve already normalised expectations for this sort of embedded cross sell. As valuable as it is, it doesn’t fundamentally change the insurance experience.
However, our new-found ability to access, analyse and act on data opens the door to a more sophisticated embedded insurance experience. Embedded Insurance 2.0, if you will. One that leverages real-time, third-party and customer data, and adds active risk mitigation.
And in a post-covid world, where we need to strike a difficult balance between ever changing risk and risk management, the new value potential offered through embedded insurance 2.0 provides some important answers to the problems insurers now face.
Embedded insurance 2.0: The next new thing
This “embedded insurance 2.0” experience is already here. By providing a dashboard view of their life, IoT devices and apps are helping people make better decisions and take action that reduces risk.
Experience economy leaders can now analyse individual customer data, including demographics, location, and incentives, with real-time data from IoT devices to influence behavior and offer highly personalised products, services, and experiences. What’s more, they can project future behaviour through the application of advanced analytics, AI, ML, smart and real-time data.
Insurers now have the same opportunity. By embracing embedded insurance 2.0, they can offer proactive risk mitigation, plus new product and services bundles that further cement customer loyalty.
In addition to offering policies and discounts on IoT devices and partnering with health and wellness app providers, one life insuretech is also incorporating data from an auto insurance carrier to gain a holistic view of customers’ risk profiles and offer discounted premiums. Celent analyst Donald Light has dubbed this cross-insurance-segment data sharing “the Great Cross-Over.”
Such insurtechs and greenfield insurers have several potential advantages over incumbents. Through direct access to people and their data, they understand peoples’ behavior and can influence their decisions in real time, as well as enjoying data-driven automated underwriting and claims.
Those are compelling differentiators. Insurance has not historically been a high-frequency of contact product and, until recently, that feedback loop to mitigate risk and communicate with insureds in real time simply hasn’t existed. This is a fundamentally different sort of relationship between insurer and insured, and a healthy one. Real relationships are formed based on a more immediate value exchange rather than on a bad day everyone really wished never happened.
Old risks, new opportunities for mitigation
One reason people are so interested in smart homes is to reduce risk. In this “embedded insurance 2.0” scenario, an insurer could incorporate all of the IoT devices in your home to identify potential zones of risk that require management and limit the damage caused should the worst happen. Roughly 50% of home insurance claims are from escape of water. At the point of installation IoT devices can give a detailed assessment of the potential risk your house has of a leak and ensure steps are taken to limit that risk. Further, when your leak-detection bot spots a leak, it could cut off the flow of water to vulnerable areas and alert you or engage a trusted plumber to avoid disaster or initiate a claim.
These are simple examples that demonstrate the power of embedded insurance 2.0 has to fundamentally change insurance offerings. This sort of ecosystem thinking is new for insurers, but there are a myriad of other mutually beneficial opportunities within that relationship model that generate both value for insureds and new revenue for insurers.
The commercial opportunities are even greater. For example, warehousing presents enormous catastrophic risk around fire, and the greatest predictor of fire risk in a warehouse is people. Here’s a scenario: an air conditioning duct is blocked, triggering an alert to the nearest maintenance person’s mobile indicating the location of the blocked duct and its priority over fixing a jammed printer. That’s beneficial to the warehouse owner and the people in the warehouse, and it’s also massively beneficial to the insurer.
In commercial real estate there are a handful of large building management systems providers. Leveraging APIs to connect to a cloud-native insurance platform, an insurer could – at massive scale – reduce the risks presented by a building and its inhabitants. .
Here’s another scenario. Huge farming ecosystems optimize seed production, alert for droughts and floods, and help farmers determine when they should fertilise or irrigate based on the weather forecast. Sensors detect the duration and intensity of a drought, and the farmer gets an automatic and predetermined payout based on loss parameters. The farmer doesn’t even file a claim. This embedded/parametric model holds enormous promise for an ambitious insurer.
These types of collaborative opportunities offer a source of real differentiation and new revenue for insurers who can respond.
The goals of embedded insurance 2.0
Importantly, the real goal of these technology-enabled business models is to rehumanise insurance and make it more relevant in more peoples’ lives, by doing more for them.
By offering meaningful, actionable, context-specific advice based on measurable behaviors, that are supplemented by anonymized comparisons with similar risk profiles, insurers have a new-found ability to understand specific customer risk and help them avoid losses.
Achieving that state offers a massive quid pro quo. Insureds pay appropriately based on their behavior and usage. They benefit further from dashboard-like access to information that helps them live healthier, safer, and more economical lives, while also lowering their risk. The insurer benefits from fewer and lower losses, and immediate FNOL. But perhaps most important, it offers the opportunity to have a positive impact on people’s lives by understanding customers, engaging more frequently and under better circumstances, and rewarding behaviors that lower losses, increase revenue, and close the insurance gap.
Achieving this more caring and effective insurance model is not some pipe dream. With a core that is engineered for data fluidity and API-first insurance core systems, seamless data collection and exchange is here, allowing ambitious insurers to become the experience-economy leaders they’ve always wanted to be.
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