Everything You Need to Know About Insurance as a Service

4 minutes, 26 seconds read

Published on Sep 18, 2018

Updated on Jul 21, 2020

The past years have seen strong traction in “as a Service” business model across several industries. The insurance industry is no different.

The idea behind XaaS, or “as a Service” is that one can buy services from vendors on a subscription-basis – depending on their needs and requirements. It is especially beneficial to reduce time to benefit, installation costs, ensure scalability and swift upgrades. XaaS often corresponds to the availability of service on the cloud.

[Read More: Everything as a Service]

Now,

What is Insurance as a Service?

Insurance as a Service implies that individuals or companies can buy pre-built elements of Insurance services on subscription-basis as per their needs and requirements.

How is Insurance-as-a-Service different from Sandbox?

The Sandbox approach emphasizes on experimenting and learning before finally adopting technology or systems to reduce the impact of failure. Whereas Insurance as a Service is a platform built after testing done on a wide user base and is available for users on a subscription basis. Insurers use a sandbox approach to test product-market fit before the actual release. Individuals, corporates, and even insurance companies can benefit from Insurance as a Service.
Details – Sandbox Approach in Insurance

What makes Insurance as a Service model impressive?

Insurance as a Service model requires only a little to no capital expenditure. The service infrastructure, owned by the provider, distributes the cost across users.

After studying business cases, primarily for incumbent processes, corporates and stakeholders can test a particular service before actually investing in it. Businesses need not overhaul their core functions for integrations. A small-scale trial can be enough to adopt a specific model. In many such ways, Insurance as a service is an excellent option for incumbents, entrepreneurs, and startups.

Prerequisites

XaaS products are, in general, scalable and can be integrated across a variety of platforms without compromising customization and customer experiences. Their infrastructure relies heavily on data, analytics and contextual tools. The fundamental requirements from Insurance as a Service infrastructure are:

1. Customer analytics

Why: Advanced analytical technologies are great to get an insight about customer psychology and implement them to create related products.

How: NLP-powered chatbots can create a transparent platform for communication with customers and dive into the functional requirements of the product.

2. Personalized data

Why: This is a high-time to humanize conversations with customers and establish a real-time personalized relationship.

How: Through the omnichannel approach, it is possible to gather and unify customer data collected from various sources like social media, website, communication with agents, to name some.

3. Contextual tools

Why: To formulate products that can match customer expectations, offer convenience and empathy-based experiences.

How: Leveraging analytics, emotion AI and NLP-based technologies to analyze customers’ intent and perceptions about your brand from multiple sources (e.g. social media, forums, etc.)

How are start-ups developing models for Insurance as a Service?

As per recent InsurTech developments, start-ups are pursuing the following 3 Insurance as a Service model:

1. Full-stack

It involves an end-to-end infrastructure to deploy digital insurance. Here, a technology company can develop a platform for Insurance processes as well as licensed white-label backend. For example, Swiss startup Stonestep provides Micro-insurance as a Service by partnering with mobile network operators, retailers, and vendors who already have an existing distribution presence.

Working with partners helps them to save infrastructure costs and helps them to make insurance available for even the most remote geographical locations.

2. Digitizing Process Assistance

Most of the incumbents still rely on legacy systems and processes for underwriting, policy distribution, claims, and agent onboarding. The Insurance-as-a-Service model also assists companies to digitize and channelize insurance operations in a single system and then connect them to their engine. Mantra Labs is a leading provider of InsurTech services and offers plug and play products for digital insurers such as:

Insurance Chatbot: An NLP-powered that works on a self-learning model and is updated from time to time based on the interactions between agents and customers. It brings unparalleled benefits in terms of ROI saving licensing and agent salaries costs.

Paper to digital document parser: Mantra Labs’ Intelligent Character Recognizer allows users to convert and store paper-based or handwritten documents into a digital format.

Today we need situation-dependent personal risk management products. Insurers can remodel their offerings based on real-time scenarios which will not only urge the customer to invest in the insurance policies but also work towards improving their customers’ health and welfare. For instance, you may not have comprehensive auto insurance. But, how good it will be if your insurer provided theft insurance whenever you enter a theft-prone area? It is a win-win situation for both — the policyholder as well as provider.

3. Digitizing Core Services

Some startups offer their services in a specific field of insurance. For instance, Mantra Labs focuses on customer engagement, new revenue streams, and security features. Some companies like Riskpossible help with underwriting, RightIndem for claims, and others for customer data management and fraud detection.

Because these companies focus on specific insurance domains they are much more efficient in making Insurance services a winner.

Mantra Labs is an InsurTech100 firm specializing in AI-first products and solutions for the new-age digital Insurers. For your specific requirements, please feel free to drop a line at hello@mantralabsglobal.com.

Further Reading:

Let’s take a trip back in time—2008. Netflix was nothing like the media juggernaut it is today. Back then, they were a DVD-rental-by-mail service trying to go digital. But here’s the kicker: they hit a major pitfall. The internet was booming, and people were binge-watching shows like never before, but Netflix’s infrastructure couldn’t handle the load. Their single, massive system—what techies call a “monolith”—was creaking under pressure. Slow load times and buffering wheels plagued the experience, a nightmare for any platform or app development company trying to scale

That’s when Netflix decided to do something wild—they broke their monolith into smaller pieces. It was microservices, the tech equivalent of turning one giant pizza into bite-sized slices. Instead of one colossal system doing everything from streaming to recommendations, each piece of Netflix’s architecture became a specialist—one service handled streaming, another handled recommendations, another managed user data, and so on.

But microservices alone weren’t enough. What if one slice of pizza burns? Would the rest of the meal be ruined? Netflix wasn’t about to let a burnt crust take down the whole operation. That’s when they introduced the Circuit Breaker Pattern—just like a home electrical circuit that prevents a total blackout when one fuse blows. Their famous Hystrix tool allowed services to fail without taking down the entire platform.

Fast-forward to today: Netflix isn’t just serving you movie marathons, it’s a digital powerhouse, an icon in platform engineering; it’s deploying new code thousands of times per day without breaking a sweat. They handle 208 million subscribers streaming over 1 billion hours of content every week. Trends in Platform engineering transformed Netflix into an application dev platform with self-service capabilities, supporting app developers and fostering a culture of continuous deployment.

Did Netflix bring order to chaos?

Netflix didn’t just solve its own problem. They blazed the trail for a movement: platform engineering. Now, every company wants a piece of that action. What Netflix did was essentially build an internal platform that developers could innovate without dealing with infrastructure headaches, a dream scenario for any application developer or app development company seeking seamless workflows.

And it’s not just for the big players like Netflix anymore. Across industries, companies are using platform engineering to create Internal Developer Platforms (IDPs)—one-stop shops for mobile application developers to create, test, and deploy apps without waiting on traditional IT. According to Gartner, 80% of organizations will adopt platform engineering by 2025 because it makes everything faster and more efficient, a game-changer for any mobile app developer or development software firm.

All anybody has to do is to make sure the tools are actually connected and working together. To make the most of it. That’s where modern trends like self-service platforms and composable architectures come in. You build, you scale, you innovate.achieving what mobile app dev and web-based development needs And all without breaking a sweat.

Is Mantra Labs Redefining Platform Engineering?

We didn’t just learn from Netflix’s playbook; we’re writing our own chapters in platform engineering. One example of this? Our work with one of India’s leading private-sector general insurance companies.

Their existing DevOps system was like Netflix’s old monolith: complex, clunky, and slowing them down. Multiple teams, diverse workflows, and a lack of standardization were crippling their ability to innovate. Worse yet, they were stuck in a ticket-driven approach, which led to reactive fixes rather than proactive growth. Observability gaps meant they were often solving the wrong problems, without any real insight into what was happening under the hood.

That’s where Mantra Labs stepped in. Mantra Labs brought in the pillars of platform engineering:

Standardization: We unified their workflows, creating a single source of truth for teams across the board.

Customization: Our tailored platform engineering approach addressed the unique demands of their various application development teams.

Traceability: With better observability tools, they could now track their workflows, giving them real-time insights into system health and potential bottlenecks—an essential feature for web and app development and agile software development.

We didn’t just slap a band-aid on the problem; we overhauled their entire infrastructure. By centralizing infrastructure management and removing the ticket-driven chaos, we gave them a self-service platform—where teams could deploy new code without waiting in line. The results? Faster workflows, better adoption of tools, and an infrastructure ready for future growth.

But we didn’t stop there. We solved the critical observability gaps—providing real-time data that helped the insurance giant avoid potential pitfalls before they happened. With our approach, they no longer had to “hope” that things would go right. They could see it happening in real-time which is a major advantage in cross-platform mobile application development and cloud-based web hosting.

The Future of Platform Engineering: What’s Next?

As we look forward, platform engineering will continue to drive innovation, enabling companies to build scalable, resilient systems that adapt to future challenges—whether it’s AI-driven automation or self-healing platforms.

If you’re ready to make the leap into platform engineering, Mantra Labs is here to guide you. Whether you’re aiming for smoother workflows, enhanced observability, or scalable infrastructure, we’ve got the tools and expertise to get you there.

Insurance as a service

What makes Insurance as a Service model impressive?