The Netherlands Insurance Landscape in a Nutshell

Published on Aug 21, 2019

Updated on Apr 3, 2020

‘What more could people want’ in a nation that already ranks highest in terms of press and economic freedom, human development, quality of life, and happiness? On another note, insurance companies and the government must have been doing something right — over 99.8% of the Dutch population is insured!

This might portray the Netherlands as a saturated market for insurance. However, while the overall Dutch populace has health insurance, there’s still scope for life, non-life and better health insurance products.

The following infographic on Netherlands’ Insurance landscape can shed some perspective.

Insurance Challenges in the Netherlands

KPMG reports, 65% of CIOs (Chief Insurance Officers) agree that the shortage of skills is preventing them from matching the pace of change. [The skills shortage here corresponds to big data, analytics, AI, enterprise and technical architecture and DevOps]

Privacy-Technology paradox is one of the main reasons for the gap between insurance products and personalization. Strict European privacy regulations create a barrier for advanced technologies that relies on data.

Insurance is on the Tech-Radar

The Dutch insurance companies are not only thriving to match the pace of change but also inclined towards investing in futuristic technology. Many of these technologies can be collectively called Artificial Intelligence. But, the impact of individual technologies and how the insurance sector is deploying them is what matters.

Current Technology Trends in Insurance in the Netherlands

Microservices

Microservices breaks down large insurance schemes to their simplest core functions. Organizations treat every microservice as a single service with its API (Application Program Interface).

Insurers in the Netherlands concur that getting into microservices architecture early can bring a bigger competitive advantage to them. Microservices in travel and vehicle insurance promises to be a great prospect in the Netherlands.

Blockchain

Blockchain corresponds to smart contracts in a distributed environment.

You might also like to read about how distributed ledgers can revamp insurance workflows.

The insurance industry is already using distributed ledgers for insuring flight delays, lost baggage claims, and is expanding to shipping, health insurance, and consumer durables domains.

Edge Computing

Edge computing brings computation and data storage closer to the consumer’s location. It improves response time and at times can take real-time actions. Autonomous vehicles, home automation, smart cities, etc. are the sectors that deploy edge computing effectively.

Insured assets with edge computing capabilities help insurers offer better deals and customized policies.

Cognitive Expert Advisors

Augmenting customer service units with AI-powered bots and AI-assisted human advisors add to the superior customer experience. The cognitive expert advisor is a combination of both.

Cognitive experts use advanced analytics, natural language processing, decision-making algorithms, and machine learning. This technology breaks the prevailing trade-offs between speed, cost, and quality in delivering insurance policies and products.

Fraud Analytics

It involves social network analytics, big data analytics, and social customer relationship management for rating claims, improving transparency, and identifying frauds.

AXA insurance has been using fraud analytics in its product OYAK to integrate all customer-related data into a coordinated corporate vision. The technology has enabled AXA to link two slightly records from the same customer preventing fraudulent instances.

AI-based Underwriting

AI-driven unmanned aerial vehicles, also known as drones can examine sites, which are otherwise extreme for humans to visit.

Using such technologies for geological surveys makes the underwriting process more accurate. Insurers are aligning their risk management strategies with AI-based underwriting.

Join our Webinar — AI for Data-driven Insurers: Challenges, Opportunities & the Way Forward hosted by our CEO, Parag Sharma as he addresses Insurance business leaders and decision-makers on April 14, 2020.

Machine Learning (ML)

ML relies on data patterns and is capable of performing tasks without external instructions. In this system, the computer listens to the customer’s data, learns from it, and begins to automatically handle similar instances.

InsurTech is leveraging machine learning to quote optimal prices and manage claims effectively. It is a cost-effective technology that works on different sets of user-persona.

Predictive Analytics

Predictive analytics studies current and historical facts to make predictions about future or otherwise unknown events.

Leading insurers in the Netherlands are using predictive analytics for controlling risks in underwriting, claims, marketing, and developing personalized products.

Predictive Analytics in Insurance Use Case: Zurich

Switzerland’s largest insurer- Zurich uses predictive analytics to identify risks that their customers are ‘actually’ going to face. Predictive analytics incorporates machine learning to anticipate events beyond statistics and probability.

The open-source machine learning model brings the organization the following benefits.

Zurich is capable of scaling analytics across the larger volumes of data generated through smart devices.
There’s a flexibility to introduce new data sources and features and test against them in real-time.
Data scientists can mix-and-match tools to experiment and curate different data sets.

Predictive analytics is Zurich’s key differentiator enabling it to move with the speed of the fastest product in the market.

For AI-based solutions, customer experience and deep-tech consulting, drop us a ‘hi’ at hello@mantralabsglobal.com.

Future Technology Trends That Have Potential to Disrupt Insurance Industry

“You’ll need other skills now. I tell my colleagues: go out, attend seminars, what closely when doing groceries. Because you can learn from a customer-centric view at any moment.”
Wim Hekstra, CEO, Aegon Wholesale

Brain-Computer Interface (BCI)

BCI allows computers to interpret the user’s distinct brain patterns. At present researchers are focusing on using BCI for the treatment of neurodegenerative disorders. This can change medical-underwriting schemes.

Human Augmentation

It refers to creating cognitive and physical improvements integral to the human body. The present-day insurance policies cover human and assets. The future calls for insurance for superhumans.

Smart Dust

It is a system of many tiny micro-electromechanical systems (MEMS). Smart dust includes a microscopic cluster of sensors, robots, cameras, etc. to identify changes in light, temperature, etc. This can help the insurance industry by triggering information against events, which are susceptible to changes.

The future brings enormous opportunities for insurers with Augmentation, AI, and Machine Learning. The insurers’ intent towards accuracy, cost-optimization, and personalized products is the driving force to experiment with technology.

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.

The Netherlands Insurance Landscape in a Nutshell

Insurance Challenges in the Netherlands

Insurance is on the Tech-Radar