Astronaut loading animation Circular loading bar

Try : Insurtech, Application Development

AgriTech(1)

Augmented Reality(20)

Clean Tech(5)

Customer Journey(12)

Design(36)

Solar Industry(6)

User Experience(56)

Edtech(10)

Events(34)

HR Tech(2)

Interviews(10)

Life@mantra(11)

Logistics(5)

Strategy(17)

Testing(9)

Android(47)

Backend(30)

Dev Ops(7)

Enterprise Solution(27)

Technology Modernization(2)

Frontend(28)

iOS(43)

Javascript(15)

AI in Insurance(35)

Insurtech(63)

Product Innovation(49)

Solutions(19)

E-health(10)

HealthTech(22)

mHealth(5)

Telehealth Care(4)

Telemedicine(5)

Artificial Intelligence(132)

Bitcoin(8)

Blockchain(19)

Cognitive Computing(7)

Computer Vision(8)

Data Science(17)

FinTech(50)

Banking(7)

Intelligent Automation(26)

Machine Learning(47)

Natural Language Processing(14)

expand Menu Filters

Disruption Vs Innovation in Insurance

3 minutes, 11 seconds read

People concerned with insurance have been using the terms- ‘innovation’ and ‘disruption’ interchangeably, perhaps because both correspond to building something ‘new’. However, there is a fine line between the two. All disruptors are innovators whereas, not all innovators are disruptors. Let’s delve deep into the difference between disruption and innovation in insurance.

Who are the ‘Disruptors’ in Insurance?

Disruptors drastically alter prevalent businesses, services, or products. They tend to be more creative, useful, impactful, inexpensive, time-savvy, and most importantly – scalable. 

As an example, Lemonade took in $57 million in premium revenue from 4,25,000 customers in 2018. This four-year-old startup was able to sell premiums to millennials- 90% of whom were purchasing insurance for the first time.

Reason- instead of an all-encompassing insurance package, Lemonade is keen on distributing micro policies as low as $5, which the customer perceives as useful. They’ve simplified the claim settlement process and within 3 minutes, a customer can get his refund credited to his account. While Lemonade sells its insurance policies through chatbot Maya, chatbot Jim handles claim settlement. Such AI-powered bots can handle multiple customer requests just as human agents and are better in detecting fraud. 

The disruptors are prone to adapt to changing customer preferences, which the traditional insurers are reluctant to because of the fear of losing existing customers. Disruption in insurance can break the barrier of the lower market penetration rate.

What’s Innovation in Insurance? 

Innovation is independent of drastic changes in businesses. It focuses more on bringing positive business development by delivering convenience to the customer and improving operational efficiency.

Innovation is not always about introducing new technology. It is also about harnessing existing technologies to build innovative solutions. For instance, blockchain technology has been there for decades; but the insurance industry has recently utilized it for algorithmic trading, smart contracts, policy distribution, and claim settlements.

For example, AXA Fizzy provides paperless flight insurance based on blockchain technology. Every user interaction is recorded and executed in the ledgers- from buying a policy to claim settlement without any human intervention. 

Other examples of innovation in insurance include Robo-advice, NLP (Natural Language Processing) to understand customer queries, insurance for IoT devices, AI-powered underwriting, automating insurance workflows, and Machine Learning technologies.

Also, read – Innovative insurance products of 2109

However, according to McKinsey’s report on Digital insurance in 2018, most of the P&C, health, and life insurance innovations revolve around marketing and less towards product development and claims. This gives an idea of the scope of innovation in insurance.

Where insurtechs are focusing

What’s Next in Insurance: Disruption or Innovation?

The traditional insurance business is known to be resilient to technological advancements and innovations in terms of consumer-centric products. To stay relevant and competitive, insurers should shift focus from digitization to strategic disruption according to the changing market dynamics.

In fact, Insurers are willing to fund insurance startups to gain a first-mover advantage in terms of technology and innovations. These investments illustrate a clear goal of improving customer experiences and supporting their existing operations at the startups’ risk. 

For instance, “Axa provided seed funding for five European start-ups under a fund set up in France in 2013, before launching Axa Strategic Ventures in 2015. The €200 million ($223.47 million) venture capital fund has the mandate to invest in innovations in insurance..”. (OECD (2017), Technology and innovation in the insurance sector)

Innovation from Insurtechs has the potential to contribute to the insurance value chain; however, managing disruption is still quite a challenge. Disruption alters the business and behaviours in such a short span that most of the outcomes remain unanticipated. While innovation takes time to catch the stream, disruption can make or kill a business. The best is to blend incumbents’ years of experience with innovation from startups to bring an accountable disruption.

We’ve been solving critical front & back-office insurtech challenges through innovative technological solutions. Drop us a ‘hi’ at hello@mantralabsglobal.com to know more.

Cancel

Knowledge thats worth delivered in your inbox

10 Analytics Tools to Guide Data-Driven Design

Analytics are essential for informing website redesigns since they offer insightful data on user behavior, website performance, and areas that may be improved. Here is a list of frequently used analytics tools to guide data-driven design that can be applied at different stages of the website redesign process. 

Analytics Tools to Guide Data-Driven Design

1. Google Analytics:

Use case scenario: Website Audit, Research, Analysis, and Technical Assessment
Usage: Find popular sites, entry/exit points, and metrics related to user engagement by analyzing traffic sources, user demographics, and behavior flow. Recognize regions of friction or pain points by understanding user journeys. Evaluate the performance of your website, taking note of conversion rates, bounce rates, and page load times.

2. Hotjar:

Use case scenario: Research, Analysis, Heat Maps, User Experience Evaluation
Usage: Use session recordings, user surveys, and heatmaps to learn more about how people interact with the website. Determine the high and low engagement regions and any usability problems, including unclear navigation or form abandonment. Utilizing behavior analysis and feedback, ascertain the intentions and preferences of users.

3. Crazy Egg:
Use case scenario: Website Audit, Research, Analysis
Usage: Like Hotjar, with Crazy Egg, you can create heatmaps, scrollmaps, and clickmaps to show how users interact with the various website elements. Determine trends, patterns, and areas of interest in user behaviour. To evaluate various design aspects and gauge their effect on user engagement and conversions, utilize A/B testing functionalities.

4. SEMrush:

Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct keyword research to identify relevant search terms and phrases related to the website’s content and industry. Analyze competitor websites to understand their SEO strategies and identify opportunities for improvement. Monitor website rankings, backlinks, and organic traffic to track the effectiveness of SEO efforts.

5. Similarweb:
Use case
scenario: Research, Website Traffic, and Demography, Competitor Analysis
Usage: By offering insights into the traffic sources, audience demographics, and engagement metrics of competitors, Similarweb facilitates website redesigns. It influences marketing tactics, SEO optimization, content development, and decision-making processes by pointing out areas for growth and providing guidance. During the research and analysis stage, use Similarweb data to benchmark against competitors and guide design decisions.

6. Moz:
Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct website audits in order to find technical SEO problems like missing meta tags, duplicate content, and broken links. Keep an eye on a website’s indexability and crawlability to make sure search engines can access and comprehend its material. To find and reject backlinks that are spammy or of poor quality, use link analysis tools.

7. Ahrefs:
Use case scenario:
Research, Analysis, SEO Optimization

Usage: Examine the backlink profiles of your rivals to find any gaps in your own backlink portfolio and possible prospects for link-building. Examine the performance of your content to find the most popular pages and subjects that appeal to your target market. Track social media activity and brand mentions to gain insight into your online reputation and presence.

8. Google Search Console:

Use case scenario: Technical Assessment, SEO Optimization
Usage: Monitor website indexing status, crawl errors, and security issues reported by Google. Submit XML sitemaps and individual URLs for indexing. Identify and fix mobile usability issues, structured data errors, and manual actions that may affect search engine visibility.

9. Adobe Analytics:
Use case scenario:
Website Audit, Research, Analysis,
Usage: Track user interactions across multiple channels and touchpoints, including websites, mobile apps, and offline interactions. Segment users based on demographics, behavior, and lifecycle stage to personalize marketing efforts and improve user experience. Utilize advanced analytics features such as path analysis, cohort analysis, and predictive analytics to uncover actionable insights.

10. Google Trends:

Use case scenario: Content Strategy, Keyword Research, User Intent Analysis
Usage: For competitor analysis, user intent analysis, and keyword research, Google Trends is used in website redesigns. It helps in content strategy, seasonal planning, SEO optimization, and strategic decision-making. It directs the production of user-centric content, increasing traffic and engagement, by spotting trends and insights.

About the Author:

Vijendra is currently working as a Sr. UX Designer at Mantra Labs. He is passionate about UXR and Product Design.

Cancel

Knowledge thats worth delivered in your inbox

Loading More Posts ...
Go Top
ml floating chatbot