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The Netherlands Insurance Landscape in a Nutshell

‘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 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 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.

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.

  1. Zurich is capable of scaling analytics across the larger volumes of data generated through smart devices. 
  2. There’s a flexibility to introduce new data sources and features and test against them in real-time.
  3. 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

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.


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Chatbots are the assistants of the future and they are taking the Internet by storm. Ever since their first appearance in 1994, the goal was to create an AI that could conduct a real dialogue with their interlocutors. The purpose is to free up customer service agents’ time so they could focus on more delicate tasks- which require a more human approach.

If you are thinking about including a chatbot on your website, here are the things you need to keep in mind to boost customer engagement and deliver high-quality services.

Define your audience

First things first- think about who will be interacting with the chatbot? Who are your customers? How do they talk? How can you address them in a way they’ll enjoy? How can you help them?

For instance, if your company sells clothes that are mostly designed for young adults, using a less formal tone will be much more appealing to them.

Lisa Wright, a customer service specialist at Trust My Paper advice: “Customer service calls are usually recorded, so listening to a few of them can be a good place to start designing your chatbot’s lines of dialogue.”

Give your bot some character

People don’t like to talk to plain, simple robots. Therefore, giving your chatbot some personality is a must. Some brands prefer naming their chatbots and even design an animated character for them. This makes the interaction more real.

For example, The SmarterChild chatbot- designed back in 2000, was able to speak to around 2,50,000 humans every day with funny, sad, and sarcastic emotions.

However, the chatbot’s character needs to match your brand identity and at the same time- appeal to customers. Think about – how would the bot speak, if they were real? Are there some phrases or words they would never use? Do they tell jokes? All these need to be well-thought through, before going into the chatbot writing and design phase.

According to a report published by Ubisend in 2017, 69% of customers use the chatbot to get an instant answer. Only 15% of them would interact for fun. Thus, don’t sacrifice the performance for personality. 

Also read – 5 Key Success Metrics for Chatbots

Revise your goals before chatbot writing

Alexa- Amazon bot has 30+ skills which include scheduling an appointment, booking a cab, reading news, playing music, controlling a smartphone, and more. However, every business bot doesn’t need to be a pro in every assisting job.

Before entering the writing phase, think over once again – WHY you need a chatbot? Will it help customer service only? Or will it also help in website navigation, purchase, return, refund, etc.?

Usually, customers want one of the three things when they visit your site: an answer to something they’re looking for, make a purchase, or a solution to their problem. You can custom build your chatbot to tackle either one or all of these three situations. Many brands use chatbots to create tailored products for their clients.  

Cover all possible scenarios

When you start writing the dialogue, consider the fact that a conversation can go in many directions. To ensure that all the situations are covered- start with a flowchart of all possible questions and the answers you chatbot can give.

To further simplify your chatbot writing, take care of one scenario at a time and focus on keeping the conversation short and simple. If the customer is too specific or is not satisfied with the bot’s response, do not hesitate to redirect them to your customer service representatives.

For instance, Xiaocle is one of the most successful interactive chatbots launched by Microsoft in July 2014. Within three months of its launch, Xiaocle accomplished over 0.5 billion conversations. In fact, speakers couldn’t understand that they’re talking to a bot for 10 minutes.

Also read – Why should businesses consider chatbots?

This article is contributed to Mantra Labs by Dorian Martin. Dorian is an established blogger and content writer for business, career, education, marketing, academics, and more.


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The antiquated commodity of Financial ‘Coverage & Protection’ is getting a new make-over.  Conventional epigrams like ‘Insurance is sold and not bought’ are becoming passé. Customers are now more open than ever before to buying insurance as opposed to being sold by an agent.  The industry itself is witnessing an accelerated digitalization momentum on the backs of 4G, Augmented Reality, and Artificial Intelligence-based technologies like Machine Learning & NLP.

As new technologies and consumer habits keep evolving, so are insurance business models. The reality for many insurance carriers is that they still don’t understand their customers with great accuracy and detail, which is where intermediaries like agents and distributors still hold incredible market power.

On the other hand, distribution channels are turning hybrid, which is forcing carriers to be proficient in their entire channel mix. Customer expectations for 2020 will begin to reflect more simplicity and transparency in their mobility & speed of service delivery.

A recently published Gartner Hype Cycle highlights 29 new and emerging technologies that are bound for greater business impact, that will ultimately dissolve into the fabric of Insurance.

For 2020 and beyond, newer technologies are emerging along with older but more progressively maturing ones creating a wider stream of opportunities for businesses.


Irrespective of the technology application adopted by insurers — real, actionable insights is the name of the game. Without it, there can be no long term gains. Forrester research explains “Those that are truly insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers by 2020”.

Based on the major trends identified in the Hype Cycle, 5 of the most near-term disruptive technologies and their use cases, are profiled below.

  1. Emotion AI
    Emotion Artificial Intelligence (AI) is purported to detect insurance fraud based on the audio analysis of the caller. This means that an AI system can decisively measure, understand, simulate and react to human emotions in a natural way.

    F0r Insurers, sentiment and tone analysis captured from chatbots fitted with emotional intelligence can reveal deeper insights into the buying propensity of an individual while also understanding the reasons influencing that decision.


Autonomous cars can also sensors, cameras or mics that relay information over the cloud that can be translated into insights concerning the emotional state of the driver, the driving experience of the other passengers, and even the safety level within the vehicle.

Gartner estimates that at least 10% of personal devices will have emotion AI capabilities, either on-device or via the cloud by 2022. Devices with emotion AI capacity is currently around 1%.

  1. Augmented Intelligence
    Augmented Intelligence is all about process intelligence. Widely touted as the ‘future of decision-making’, this technology involves a blend of data, analytics and AI working in parallel with human judgement. If Scripting is rules based automation, then ‘Augmenting’ is engagement and decision oriented.

    This manifests today for most insurance carriers as an automated back-office task, but over the next few years, this technology will be found in almost all internal and customer facing operations. Insurers can potentially offer personalised services based on the client’s individual capacity and exposure to risk — creating opportunities for cross/up-selling.

Source: Gartner Data Analytics Trends for 2019

For instance, Online Identity Verification is an example of a real-time application that not only enhances human’s decision making ability, but also requires human intervention in only highly critical cases. The Global value from Augmented AI Tools will touch $4 Trillion by 2022.

  1. AR Cloud
    The AR Cloud is simply put a real-time 3D map of an environment, overlayed onto the real World. Through this, experiences and information can be shared without being tied down to a specific location. Placing virtual content using real world coordinates with associated meta-data can be instantly shared and accessed from any device.

    For insurers, there is a wide range of opportunities to entice shopping customers on an AR-Cloud based platform by presenting personalized insurance products relevant to the items they are considering buying.

    The AR ecosystem will be a great way to explain insurance plans to customers, provide training and guidance for employees, assist in real-time damage estimation, improve the quality of ‘moment-of-truth’ engagements. This affords modern insurance products to co-exist seamlessly along the buying journey.

  2. Personification
    Personification is a technology that is wholly dependent on speech and interaction. Through this, people can anthropomorphize themselves and create avatars that can form complex relationships. The Virtual Reality-based concept will be the next way of communicating and forming new interactions.

    VR Applications such as  accident recreation, customer education and live risk assessment, can help insurers lower costs for its customers and personalise the experience.

    Brands have already begun working their way into this space, because as they see it — if younger generations are going to invariably use this technology for longer portions of their day for work, productivity, research, entertainment, even role-playing games, they will shop and buy this way too.

  3. Flying Autonomous Vehicles and Light Cargo Drones
    Although this technology is only a decade away from being commercially realized, the non-flying form is about to make its greatest impact since its original conception. Regulations are the biggest obstacle to the technology taking off, while its functionality continues to improve.

    The Transportation & Logistics ecosystem is on the brink of a complete shift, which will create a demand for a wide array of insurance related products and services that covers autonomous vehicles and cargo delivery using light drones.

While automation continues to bridge the gaps, InsurTechs and Insurance Carriers will need to embrace ahead of the curve and adopt newer strategies to drive sustainable growth.

Mantra Labs is an InsurTech100 company solving complex front & back-office processes for the Digital Insurer. To know more about our products & solutions, drop us a line at


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