Embedded Insurance: How Real-Time Data is Changing the Insurance Game

Embedded insurance is a hot topic in insurance right now, and is a type of insurance that is integrated into a product or service. If you’ve ever been prompted to add Travel Insurance to your holiday booking, or stick gadget insurance on to an Amazon purchase, you’ve been exposed to embedded insurance. It involves using real-time data to offer personalised coverage, and post-bind can help mitigate risks or streamline the claims process. According to a report by ResearchAndMarkets, the global embedded insurance market size is expected to reach $110.5 billion by 2027, growing at a CAGR of 8.5% from 2020 to 2027 – so it’s a obligatory here to describe it as a “massive opportunity” for Insurers and InsurTechs.

To maximise this opportunity, however, efficient data exchange is essential. Embedded insurance is usually high-volume, low premium: travel insurance around $4-10 a day, device insurance around $5-10 a month. This is a sector of the market where “spreadsheet addiction” is a huge drag on profitability and informed underwriting and makes effective risk mitigation impossible.

Simply knowing what risks an insurer is exposed to, and the expected premium, is difficult when there are huge daily volumes of low-premium transactions if the data exchange is not correct.

A salient point regarding embedded insurance is that the data at bind is always digital – that’s the whole point. The customer is on a digital platform able to assess their potential need for insurance and offer it. The de-digitisation that often occurs in the value chain between distribution and capacity is damaging and unnecessary.

With automated and digital data exchange between distribution and capacity, the insurer always has exposure certainty, and can offer value-add risk mitigation services. This can involve collecting, analysing, and sharing data in real-time, whether from sensors or connected devices. This data can be used to understand the risks involved in insuring a particular product or service and to customise coverage based on the individual's needs.

One of the primary benefits of efficient data exchange in embedded insurance is risk mitigation. By using real-time data, insurers can identify potential risks and take proactive steps to prevent losses. For example, if a home insurance policy is embedded into a smart home system, insurers can monitor the temperature and humidity levels in the house to prevent damage from mould or water leaks. This can help reduce claims costs and improve customer satisfaction – the insurer benefits from lower loss ratios and “sticky” customers, improving the “Customer Lifetime Value” to the insurer.

Insurers with legacy systems that cannot receive data in real-time about the policy sale and the in-force risk will never be able to maximise the opportunity embedded insurance presents. The distribution side has seen a lot of investment and activity – the sale is usually friction-free to the customer. But once that sale has been made, it is essential that insurers can receive that data in real time.

That’s one of the things we offer at distriBind. Insurers can offer their distribution partners a single integration point for all their products, and receive the data in real time. The data is analysed and validated at source, premiums reconciled. Data can be pulled in from additional sources pre-and post bind to support informed underwriting and effective risk mitigation.

Curing the insurance industry of its spreadsheet addiction is our mission at distriBind. If you want to maximise the opportunity of embedded insurance but you’re encumbered by legacy systems preventing efficient data exchange, we might be just the therapy you need.