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The 5 hidden problems for Insurtech

For Insurance giants, the marketplace is changing. For young insurtechs trying to displace these giants and keen on disrupting the landscape altogether; the next big market is becoming plain and obvious: Millenials and the generations that will follow them.

A new wave of AI-driven technologies is making subtle changes to the way young people are re-thinking the whole “Why do I need insurance again?” decision.

Millennials —  are most likely to purchase insurance through an app with a few taps on their smartphones — are driving less frequently than previous generations — thereby creating a market for lower cost, pay-per-mile auto insurance. 

Yet, despite the proclivity of this demographic to stay away from ownership (and, with that, the need for coverage), they do own assets that they want insured. Insurtech is well poised above all else, to satisfy their unique coverage needs.

A majority of the World’s insurance purchases are done physically (in-person), while only a small portion of sales comes from either the web or mobile – yes, even in 2019 and for the foreseeable future, that remains true.

The Hidden Problems of Insurtech

The ‘Insurtech’ model can be broken down into — those that operate at the broker-level, those that offer insurance services/products or product-level, and those that have a hybrid approach (such as peer-to-peer insurtech) that has an insurance product with a strongly linked brokerage aspect to it. Here is a look at the challenges that surround young companies operating in these models.

#1 Partnerships are stark & sparse

For existing incumbents, the advantage is obvious — seize on the hype created by insurtech upstarts, who are capturing previously untapped audiences towards new & innovative products. 

Also, read – Top Innovative Insurance Products of 2019

Large insurers will even venture into setting up their own start-ups; or invest in new technologies within their own business.  However, despite the mutual benefit-for-all reasoning behind partnerships, these are spread thin across most regions.

Without the support of a large insurer or two, insurtechs will find it hard to manage the unit economics of the policies they sell; which brings to question the sustainability of this model for scaling.

#2 Innovation beyond downstream distribution

Insurtechs that have either chosen not to partner/ not managed to attract the right partnership with large insurers — arguably face greater challenges. Most of the insurtech-startup funding pool has moved into distribution, and rightfully so.

Distribution has brought about long-awaited changes to delivering new products and customer experiences — aspects of the business that Insurance giants consistently struggle to produce in.

Insurance, however, has four fundamental units: the underwriting of insurance, claims servicing, regulatory overhead, and distribution (actual selling).

As these insurtechs grow, the looming question remains: how will they manage the other parts of insurance, if all the money has gone into refining one stream?. For example, are they sufficiently capable of handling claims and underwriting as the business scales? These questions are yet to be answered, and the models are yet to be proven.

#3 Frequent changes to the legal & regulatory framework

“Not all insurtech businesses qualify as insurance companies” since they depend on the type and extent of the services provided. A regulatory distinction is essential to separate them — without which a reliable guarantee cannot be given to customers in the event of a loss.

Legal and regulatory commitments change with region and country, hence insurtechs are typically unsuitable for covering potentially large losses. 

#4 Attitudes of the next generation

Younger generations are less likely than previous ones to pay heed to the importance of insurance. They simply do not see it as an important financial instrument. These challenges have plagued the industry for several decades, and insurtechs will have to assume this challenge for themselves as well. At its core, insurance is a hard product to sell, no matter how good the package looks.

Technology in insurance and advancements to customer experiences are making the furthest inroads, the industry has ever seen. Yet, low insurance penetration levels are still an indicator of how difficult it is for insurtechs to find adoption among the masses.

#5 Intelligent Customer-Experiences

Thanks to Big Tech (like Google, Amazon, Apple, etc.) — customer experience has evolved rapidly. Digital products and services are now highly customisable and can be delivered at a high quality consistently. Yet, it has taken until now for the same to slowly seep into insurance. Sensing a huge opportunity, Big Tech has started moving into the insurance on-demand space, which has forced the larger insurers to adapt quickly. 

Insurtechs, who are by-default product- and tech- first, tend to fare better than their much larger counterparts. Yet challenges with data will persist. Just how well insurtechs are using data, remains to be seen. 

Will technology in insurance have to face a test of time?

The use of exceptional data and advanced analytics can help link the behavioural characteristics of customers and their spending habits – true fodder for machine learning models. How will insurtechs leverage useful insights to tackle age-old insurance selling challenges, such as intention to abandon, the propensity to purchase, or the right communication channel — will be the true test of competitive advantage.

Mantra Labs is a deep-tech advisor & consultant for young Insurtechs helping them create a strategic vision and an agile evolution road-map that addresses challenges from scaling to delivery. To learn more, reach out to us at


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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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