June 7, 2025
The insurance industry is transforming fast. MCP (Model Context Protocol), AI, and embedded insurance are working together to make buying and managing insurance quicker, smarter, and easier. Here's what you need to know:
These technologies are reshaping industries by making insurance more accessible, secure, and tailored to individual needs. Ready to see how they work? Keep reading to explore their impact and practical applications.
In November 2024, Anthropic introduced MCP, an open standard designed to link AI models to data and tools through a single, unified interface. This innovation quickly gained traction, with major players like OpenAI and Google DeepMind committing to its use [3].
Before MCP, integrating different AI models with various data sources was a complex and resource-intensive process, often referred to as the "M×N problem" - where M models required custom connections to N data sources. MCP simplifies this challenge by turning it into an "M+N" scenario, offering a universal connection standard that eliminates the need for countless custom integrations [2].
"MCP is an open standard designed to connect AI models with the data and tools they need in a uniform way. It's like a universal adapter that lets AI assistants plug into various systems. So, instead of building a custom connector for every database, API, or file system, you have one universal interface that plugs your AI into any data source."
- Sadashiv Borkar, Senior Data Scientist at Persistent [1]
The protocol operates on a client-server architecture with three main components: the Host (the AI application), the Client (handling connections), and the Server (providing access to specific resources or tools) [1]. This setup eliminates the need for custom coding when connecting to individual tools, making AI integration much more efficient. MCP is maintained as an open-source project on GitHub [3], and its transparent, community-driven approach has fueled its adoption across multiple industries, including insurance.
This universal standard is revolutionizing how insurance systems handle operations.
MCP allows AI systems to securely and efficiently access diverse data sources without requiring custom-built integrations [1]. This is particularly valuable in claims processing, where AI needs to pull information from policy documents, medical records, repair estimates, and regulatory databases all at once.
By enabling real-time access to relevant data, MCP enhances the AI's ability to understand context and make decisions. For example, in credit risk assessment, AI can seamlessly retrieve and analyze credit reports, income statements, and market trends using a single protocol [1].
The results are transformative for claims and risk processing. MCP helps AI systems handle tasks like claims intake, fraud detection, and policy updates with greater accuracy and speed, reducing manual intervention and cutting down processing times [4]. For insurance companies, this means AI can function more independently while still adhering to strict security and compliance standards required in financial services. Plus, MCP's standardized framework makes it easier to scale AI solutions across different insurance products and business areas without needing to rebuild integrations from scratch.
APIs are transforming how insurance companies seamlessly integrate coverage into their platforms without overhauling their entire tech infrastructure. By enabling automated communication between systems, APIs streamline processes and enhance efficiency across the board [5].
"APIs are the superpower the insurance industry has been waiting for." - Budhaditya Bhattacharya, Product Education, Community Engagement, and Open-Source Ecosystem Expansion at Tyk [7]
The impact of APIs is hard to ignore. They can reduce policy issuance timelines by as much as 30% [10]. Plus, with 70% of insurers acknowledging the benefits of smoother data exchange, customer satisfaction is also on the rise [10]. APIs also cut down data entry errors by up to 40%, eliminating repetitive tasks across platforms [10]. Considering the average agency uses six different systems - and carriers often manage even more - APIs ensure these tools work together seamlessly [6].
By automating tasks like policy issuance and claims processing, APIs not only speed up operations but also improve accuracy [5]. These advantages form the foundation for the three main API integration methods used in embedding insurance.
When embedding insurance products, businesses can choose from three integration approaches, each with varying levels of customization and technical effort.
The right choice largely depends on your technical capabilities and goals. Notably, providing insurance options at the point of sale can boost purchase intent by 32% [8]. Building on these integration methods, the following section dives into the technical framework required for scaling MCP-powered systems.
Using API-driven models, MCP-powered insurance systems can scale effectively with careful planning around tool registration, user authentication, and compliance. The MCP framework simplifies this process by standardizing connections, eliminating the need for custom integrations with every data source.
Start by identifying clear objectives for your system, such as improving data accuracy or reducing processing times [10]. A cloud-based technology stack often works best for connecting various tools seamlessly [10]. Companies that adopt microservices architecture, for example, report a 30% increase in deployment frequency [10], making it a strong choice for insurance platforms.
Insurance systems operate under strict regulatory guidelines. Ensure your APIs meet financial regulations like AML and KYC requirements [5]. Security measures such as multi-factor authentication, role-based access control, and data encryption (both in transit and at rest) are essential [9][10]. Failing to comply with regulations like GDPR can result in hefty fines averaging $20 million or 4% of annual revenue [10].
To enhance security, implement continuous API monitoring to detect unusual activity that could signal a breach [9]. Use sandbox environments for rigorous testing before production deployment [5]. Companies with robust security policies experience up to a 70% reduction in data breaches [10].
Plan for iterative testing throughout development [10]. Real-time monitoring tools can track performance metrics like response times and error rates. To handle traffic efficiently, use load balancing and cloud-based solutions for flexible scaling [10].
Automated testing can cut release times by 20% [10]. Additionally, organizations that use monitoring tools report a 30% drop in errors and up to a 50% improvement in response times [10].
The MCP framework streamlines this entire process by providing a standardized way for AI systems to access diverse data sources - ranging from policy documents to regulatory databases - without needing custom integrations for each connection [1].
Alongside API-driven models and the standardization offered by MCPs, no-code tools are reshaping how insurance applications are built and customized. These platforms remove technical hurdles by using visual interfaces and configurations instead of traditional coding, making embedded insurance easier to implement [11].
The adoption of no-code solutions is growing rapidly. By 2025, 70% of new business applications are expected to rely on low-code or no-code technologies, a significant jump from less than 25% in 2020 [11]. The global market for low-code platforms is forecasted to hit $65 billion by 2027 [12], underscoring the demand for tools that simplify application development.
"Insurance companies need digital solutions that play well with their legacy systems, allowing them to dismantle outdated platforms incrementally instead of enduring the cost and risk involved with a mass overhaul of the entire infrastructure. By using a low-code application platform, companies can tailor and develop their own applications to best accommodate their needs."
No-code tools empower insurers to modernize their technology stacks without requiring large budgets or extensive development teams. These platforms let non-technical teams quickly build, customize, and deploy applications [12] [13].
When paired with streamlined API integrations, no-code platforms make insurance application development even more efficient.
Visual no-code platforms bring a fresh approach to insurance integration. Their drag-and-drop editors make application development accessible to anyone, regardless of technical expertise. These user-friendly tools allow teams to design customer journeys, adjust branding, and create tailored product recommendations through simple workflows.
"No-code platforms put tech in the hands of insurance people on the front line of pricing decisions, distribution decisions, and data-enrichment decisions. This tech enablement helps insurers transform front-end consumer experiences at speed and low cost."
The real-world results speak for themselves. A Canadian MGA used a no-code platform to launch over 25 products in its first year. With minimal guidance, the team created multiple products, rates, and front-end experiences, generating over $20 million in written premiums that year. They anticipate surpassing $100 million within three years [15].
These platforms are also ideal for tailoring offerings to different customer segments. Insurers can quickly adjust coverage levels, premiums, and other policy details to meet specific needs [12]. Their adaptability allows companies to make changes without heavy coding, ensuring they can respond quickly to market demands and regulatory updates [11].
Pre-built components can dramatically speed up implementation by offering ready-to-use widgets for common insurance functions. These include tools like quote forms, policy management dashboards, claims tracking systems, and customer self-service portals, all of which can be deployed with minimal setup.
The applications of these components are wide-ranging. For instance, an insurer can launch a claims intake chatbot within days, enabling 24/7 data collection for first-notice-of-loss cases. This reduces the workload for adjusters and improves customer satisfaction [16]. Similarly, a mid-sized carrier could roll out a usage-based auto insurance product in just weeks by designing workflows, rating engines, and billing rules with minimal IT involvement [16].
Regional insurers also benefit from the multilingual capabilities of no-code platforms. For example, one regional insurer developed a bilingual portal that allowed customers to view policies, make payments, and report claims in their preferred language - all within a few weeks of starting the project [16].
When choosing a no-code platform for embedded insurance, it’s essential to look for solutions with pre-built templates and components designed for insurance-specific needs [11]. Platforms with open standards and robust API support are also critical for maintaining flexibility as businesses grow and evolve [13]. To ensure success, companies should provide thorough training and support for both technical and non-technical teams [11]. This helps maximize the platform’s potential while staying aligned with industry regulations [14]. The ability to deploy these ready-made components quickly and effectively strengthens the integration of embedded insurance into modern digital ecosystems.
The combination of MCP, AI, and embedded insurance is reshaping industries by driving revenue, increasing customer retention, and offering deeper data insights. Embedding insurance directly into platforms has proven to be a game-changer. For context, the global embedded finance market is expected to surpass $588 billion by 2025, with over 65% of digital platforms anticipated to include at least one embedded finance feature by that time [18].
This shift is particularly evident in sectors like e-commerce, mobility, travel, and automotive.
E-commerce platforms are at the forefront of adopting embedded insurance. Many leading retailers now allow customers to add gadget insurance or instant credit options seamlessly during checkout. For instance, when purchasing electronics, buyers can opt for device protection with just a few clicks, creating a streamlined and mutually beneficial experience [18].
In the mobility sector, platforms like Uber have embraced embedded insurance to support their workforce. By offering driver microloans and vehicle insurance, Uber has significantly improved retention among its gig workers [18].
For travel companies, embedded insurance enhances the booking experience by offering peace of mind. Travelers booking flights can easily add travel insurance without navigating away from the platform, ensuring instant coverage confirmation and a frictionless process [17].
The automotive industry is also leveraging embedded insurance to simplify the car rental experience. Customers can now obtain insurance directly at the point of rental, eliminating the hassle of separate purchases and making the process more convenient [19].
"Embedded finance means financial services like payments, loans, or insurance are built directly into apps and websites that aren't banks."
- Hazel Watson [17]
A standout example comes from AXA Luxembourg, which partnered with Cap4 Lab and MuleSoft to streamline claims management. By automating processes and developing six APIs to connect their systems, they reduced project delivery times by threefold and cut manual work by 25%. The API-led approach allowed them to complete integrations in just 12 weeks, compared to the 18 weeks required with custom coding [22].
To gauge the success of embedded insurance initiatives, companies rely on specific key performance indicators (KPIs) that reflect both operational efficiency and customer satisfaction. The global InsurTech market, valued at $5.45 billion in 2022, is projected to grow at an annual rate of 52.7%, reaching $82.3 billion by 2029 [20].
Some critical KPIs include:
Beyond these metrics, companies benefit from enhanced data quality and operational improvements. Embedded insurance systems provide richer customer insights and automate repetitive tasks, freeing up resources for other priorities. Forrester also forecasts an 8% increase in tech spending within the insurance sector by 2025, fueled by investments in advanced analytics and AI [21]. This growing focus highlights the potential of MCP and AI to transform embedded insurance, driving both revenue and customer engagement to new heights.
Developing MCP-powered embedded insurance systems means navigating a maze of regulations while ensuring top-notch security. The fusion of AI, insurance, and data protection brings unique challenges that demand proactive compliance and security measures. Below, we break down the key regulatory requirements in the U.S. and outline essential security practices for MCP deployments.
In the U.S., embedded insurance operates under a complex web of state and federal regulations. State insurance departments, along with agencies like the National Association of Insurance Commissioners (NAIC) and the Consumer Financial Protection Bureau (CFPB), oversee compliance. Companies must either secure licensing in all 50 states and Washington, D.C., or partner with a licensed producer who handles compliance requirements.
Providers are expected to meet stringent standards, including clear disclosures, adherence to anti-rebating laws, fair underwriting practices, and avoiding tie-in sales. MCP-powered systems must also comply with data protection, cybersecurity, and AI-related regulations to remain within the legal framework [46–48].
MCP's ability to integrate multiple data sources makes it highly adaptable but also introduces unique security challenges. Many current implementations fall short of enterprise-grade server protection [23]. As Muayad Ali, Director of Engineering, points out:
"Security for agent-tool protocols must start with strong auth, scoped permissions, and input/output validation" [23].
To address these vulnerabilities, companies should implement robust security measures like strong authentication, granular access controls, and strict input/output validation. Rate limiting is another essential practice to prevent overuse or denial-of-service attacks.
Real-time monitoring and logging are critical for detecting potential threats and maintaining detailed audit trails. This is especially important as 93% of organizations acknowledge the risks posed by generative AI, yet only 9% feel equipped to handle them [24]. Human oversight in sensitive operations can add an extra layer of security, while aligning MCP security protocols with established governance frameworks - backed by regular audits - can help identify and fix vulnerabilities before they become major issues [23][25].
The benefits of these measures are clear. For instance, a leading European insurer saved $2 million annually in compliance costs, cut capital reserve overestimates by 15%, reduced reporting errors by 90%, and sped up submission cycles by 70% [26]. These examples highlight how robust compliance and security practices can drive efficiency and cost savings while reducing risks.
The combination of MCP, AI, and embedded insurance presents businesses with a straightforward way to modernize operations while improving customer experiences. As highlighted earlier, MCP's standardized interface simplifies data access and speeds up decision-making processes. Sam Altman, CEO of OpenAI, captures this excitement perfectly: "People love MCP and we are excited to add support across our products" [28]. This sentiment reinforces MCP's ability to streamline AI integrations and open up new revenue opportunities.
To leverage MCP effectively, start by identifying inefficiencies in your current systems. Conduct an audit to locate outdated or underperforming connectors that MCP can enhance. With the embedded insurance market growing rapidly, improving integration efficiency is key to staying competitive.
Begin with a pilot program - target low-risk, high-value systems to test MCP’s impact. Once proven, establish clear best practices and governance frameworks to guide further AI integration. Strengthen monitoring and logging capabilities to ensure compliance with IT and security standards. Implement role-based access controls and audit logging to meet regulatory requirements in production environments.
Leverage advanced analytics to boost product adoption and refine your offerings. Build capabilities for rapid prototyping and data-driven product management to stay agile. Ericson Chan, Group Chief Information and Digital Officer at Zurich, notes that "Artificial intelligence (AI) can make many aspects of embedded insurance 'more productive'" [27]. Encouraging a culture of innovation will support the scalable automation strategies discussed earlier, ensuring seamless alignment with API-driven efficiencies.
Finally, focus on automating your value chain to create leaner operations. Prioritize core metrics like pricing accuracy to drive measurable results. With MCP's standardized approach to AI integration, your company is well-equipped to embrace the embedded insurance revolution while delivering outstanding customer experiences.
The Model Context Protocol (MCP) is transforming how AI operates in the insurance industry by offering a standardized way to access and integrate data. This framework allows AI systems to seamlessly connect with multiple tools and data sources, reducing context loss and enabling real-time data processing.
By simplifying workflows and cutting down on inefficiencies, MCP empowers insurers to automate key tasks such as claims processing, underwriting, and customer support. Plus, it prioritizes secure and compliant data handling, ensuring faster decisions, greater accuracy, and a smoother experience for customers.
Embedded insurance offers undeniable advantages for both businesses and consumers. For businesses, it’s a straightforward way to increase revenue by improving conversion rates and keeping customers engaged. By weaving insurance into the purchasing process, companies can reduce customer acquisition costs and build stronger brand loyalty. Why? Because customers appreciate the ease and added value. For instance, businesses that provide embedded insurance often notice higher satisfaction and engagement from their users.
On the consumer side, embedded insurance makes life simpler. It provides tailored coverage right at checkout, cutting out the hassle of separate transactions. This kind of convenience ensures the options are relevant and easy to understand. Shoppers value this personalized approach, which not only builds trust but also encourages long-term loyalty.
No-code tools and API-driven models have simplified the process of adopting embedded insurance solutions, removing the barrier of requiring advanced programming skills. With no-code platforms, companies can design and roll out insurance products quickly, slashing both development time and costs.
APIs play a key role by enabling real-time data sharing between insurance services and business platforms. This integration enhances customer experiences, smooths out operations, and embeds insurance offerings directly into the customer journey. These technologies work hand-in-hand to make insurance more accessible, streamline workflows, and boost revenue potential.