Unpacking the embedded insurance revolution
Embedded insurance (also known as “insurance-as-a-service) is a new type of insurance distribution model that’s driving a massive paradigm shift within the industry. According to InsTech London, the market for embedded insurance is set to reach a total of $722 billion in Gross Written Premiums (GWP) by 2030.
This blog post delves into the world of embedded insurance, exploring its definition, mechanics, market drivers, benefits, challenges, industry impact, and future outlook.
The definition and mechanics of embedded Insurance
Embedded insurance allows consumers to buy coverage as part of the purchase process of other goods or services. For example, damage protection for electronics during purchase on an e-commerce platform or in the store, travel insurance while booking online flights or hotels, and car insurance with vehicle purchases at dealerships.
Embedded insurance can also be transparent to the consumer. For example, Uber drivers receiving free insurance coverage as part of their contract.
Essentially, this type of distribution model relies on the innovative use of technology to incorporate insurance products and services into third-party products and services. Four of the key technological advancements enabling this integration are:
- APIs, which allow different software systems to communicate with each other. This enables insurance offerings to be integrated into the transaction flows of various online platforms and services. For example, a travel site can use an API to connect with an insurance provider's system, allowing customers to add travel insurance to their purchase with just a few clicks.
- Data analytics, which plays a large role in the customization and personalization of embedded insurance offerings. By analyzing customer data, insurance providers can offer tailored insurance coverage that meets the needs of the consumer.
- IoT, which is used in some industries (such as automotive and home insurance) to collect real-time data, including usage patterns and risk exposure. This data can help assess risk and influence the price of policies.
- AI and machine learning, which can process vast amounts of data to offer the most appropriate coverage to the consumer at the moment they make their purchase.
The driving forces
Three of the major drivers behind the growth of embedded insurance are consumer demand, increased online purchasing, and the rise of the gig economy.
- Consumer demand: It’s simple: Customers don’t want to have to buy insurance separately, with all the time and effort that requires. Instead, they want a fast, simple, streamlined, customized process that’s integrated into their daily lives. They want to be able to easily buy the coverage that meets their needs, when they need it.
- Increased online purchasing: The digital transformation of retail and the rise of e-commerce have completely changed consumer purchasing habits. According to Tidio, 70% of the US population shop online. Online platforms have proven to be an ideal environment for embedding insurance.
- The rise of the gig economy: As the gig economy grows, such as Uber and Wolt, so do the unique needs of gig workers, who often require flexible and highly customized insurance solutions that they struggle to access via traditional insurance models. The technology around embedded insurance is precisely what allows it to meet these needs.
Balancing the benefits and challenges
While the embedded insurance model offers massive benefits for consumers, it also poses unique challenges for insurers.
How consumers benefit
- Cost savings: According to InsTech London, after claims, distribution is the biggest cost for insurers. By moving distribution online and within the purchase process for other products, while streamlining the process, insurers can reduce overhead significantly. This, in turn, allows insurers to drop their own prices.
- Better access: The nature of embedded insurance makes it more widely available to a far larger population cohort than traditional distribution models. This will also help to close the protection gap, ensuring that people get the insurance coverage they really need.
- Personalized coverage: Data analytics facilitates insurance coverage that’s closely tailored to the consumer’s personal needs and risk profiles.
Challenges for insurers
- Regulatory compliance: In addition to having to navigate the complex regulatory and reporting requirements involved in new types of distribution, insurers also need to find the balance between a fast and simple consumer journey, and meeting legal and regulatory requirements.
- Data privacy concerns: Data is an inherent part of embedded insurance processes. With cyber threats on the rise, insurers need to implement and continuously optimize robust and stringent data management and security measures to protect their customers’ privacy.
- Big tech: As insurers struggle to find and leverage the right technical and data capabilities, tech companies are starting to fill the gap.
The impact of embedded insurance
The advent of embedded insurance is creating ripples across the insurance industry, affecting both traditional companies and startups, while also drawing attention from regulatory bodies.
Impact on traditional insurance companies
Embedded insurance presents traditional insurance companies with both a challenge and an opportunity. On one hand, they need to adapt to this new paradigm, which can mean “rebuilding” their existing business models and investing in new technologies. On the other hand, there’s a major opportunity to enter new markets and expand their customer base.
Impact on startups
Embedded insurance has been a massive opportunity for startups in the insurtech space. Not only do they already have an understanding of the regulatory environment, but these companies are tech-driven, making it easier for them to shift into this space and offer integrated, user-friendly embedded insurance solutions.
Response of regulatory bodies
Regulatory bodies are closely monitoring the rise of embedded insurance. Their main concerns are around consumer protection, data privacy, and compliance with existing insurance regulations and laws. Insurers can expect the evolution of the regulatory landscape to accelerate in order to address new distribution models. As a result, insurers will need to be extremely agile in order to remain compliant.
Future outlook for embedded Insurance: Sector growth and technological evolution
The future of embedded insurance looks promising, with massive growth expected across various sectors, as well as emerging technologies significantly contributing to this growth.
Growth across sectors
With the rise in the popularity of connected cars, growth in embedded insurance is expected to follow. Insurance policies can be integrated into the purchase process for new vehicles, offering tailored coverage based on driving behavior and vehicle usage (which can be monitored).
Embedded insurance can provide homeowners with more streamlined and personalized insurance options during the property buying process. These customizations could also include coverage for property damage, natural disasters, and even mortgage insurance.
As embedded insurance becomes widespread online, it’s expected that the brick-and-mortar retail industry will follow suit. This can cover a wide range of products, from electronics to appliances, offering customers instant coverage when they make the purchase.
Influence of emerging technologies
Artificial Intelligence (AI)
AI models can be trained on vast amounts of data in order to assess risk, price coverage accurately, and personalize insurance offerings, as part of the embedded insurance flow.
Internet of Things (IoT)
IoT technology, which enables real-time data collection, can help to adapt embedded insurance coverage to both the consumer’s needs as well as their risk profile. For example, sensors in connected cars can monitor usage data to ensure that consumers are, in fact, driving their cars in accordance with their risk profile. This type of technology can also facilitate insurance coverage that fluctuates according to usage.
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