Try : Insurtech, Application Development

AgriTech(1)

Augmented Reality(20)

Clean Tech(8)

Customer Journey(17)

Design(43)

Solar Industry(8)

User Experience(66)

Edtech(10)

Events(34)

HR Tech(3)

Interviews(10)

Life@mantra(11)

Logistics(5)

Strategy(18)

Testing(9)

Android(48)

Backend(32)

Dev Ops(11)

Enterprise Solution(29)

Technology Modernization(7)

Frontend(29)

iOS(43)

Javascript(15)

AI in Insurance(38)

Insurtech(66)

Product Innovation(57)

Solutions(22)

E-health(12)

HealthTech(24)

mHealth(5)

Telehealth Care(4)

Telemedicine(5)

Artificial Intelligence(143)

Bitcoin(8)

Blockchain(19)

Cognitive Computing(7)

Computer Vision(8)

Data Science(19)

FinTech(51)

Banking(7)

Intelligent Automation(27)

Machine Learning(47)

Natural Language Processing(14)

expand Menu Filters

AI and The Gen Z Experience

4 minutes read

IRDAI InsurTech Event titled- ‘InsurTech -Catalyst that inspires’ concluded on May 30th in Bengaluru. The event aimed to emphasize on InsurTech ecosystem and its benefit for insurers and saw participation from leading companies like Policybazaar, Shri Ram General Insurance, Reliance General Insurance, and Mantra Labs to name a few. IRDAI chairperson, Mr. Debasish Panda highlighted on the insurance and Insurtech partnerships and the significant role that InsurTechs can play in assisting Indian insurance sector to grow. Parag Sharma, CEO Mantra Labs, was invited as a guest speaker at the event to talk about AI and The Gen Z Experience. 

Parag Sharma, CEO Mantra Labs, at IRDAI InsurTech event.

Here are the key takeaways:

  1. Insurtech 3.0 is all about ‘Experience Economy’. With evolving customer expectations, the real challenge for the insurance industry is getting a product faster. Digital customers today want to buy an experience rather than just a product or a service. Partnering with Insurtechs would give insurers much-needed tech capabilities for product innovation. 
  1. Gen Z places importance on customer experience in various decision-making areas and their willingness to pay a premium for a better experience. In fact, CX is the deciding factor in the buying decision for Gen Z. 
PwC report on Future of Customer Experience Survey
  1. Leveraging technologies such as AI, computer vision, predictive analytics, NLP, OCR across the insurance life cycle to create a superior Gen Z experience.
How to create Value across customer lifecycle through AI & Analytics

Stage 1: Consider and Evaluate 

Data plays a key role in risk evaluation, decision-making process, and improving customer experience. Predictive behavioral analytics helps in identifying consumer patterns and the intent of those behaviors. Insurers need to forecast customer expectations based on historical pattern to improve satisfaction scores and boost revenue per customer.

The ‘Digital Behavioral Intelligence Tool’ by Formotiv helps insurers decipher user motivation and intent scores. They collect roughly 5,000-50,000 behavioral data points from 140+ different features on each individual application and provide personalized product recommendations

Stage 2: Buy and Experience

Speed is what the new customer segment wants. Insurers will need to leverage advanced AI and workflow management to improve onboarding experience for the customers. 

Leveraging advanced AI and workflow management to improve onboarding experience for the ‘want-it-now’ customers.

Stage 3: Improving underwriting through AI-Based Dynamic and Smart Decision making in real-time.

Artivatic has introduced a next-gen smart underwriting cloud–AUSIS which helps to connect, and integrate existing or third-party applications and APIs for end-to-end process.

Arivatic Insurtech & Healthtech Platform

Source: Artivatic Insurtech & Healthtech platform

Stage 4: Payment & Claims Management

Fraud Detection with AI and ML models. 

Anadolu Sigorta recently tested a predictive fraud detection system. This detection engine uses automated business rules, self-learning models, predictive analytics, text mining, image screening, device identification, and network analysis that deliver immediate, actionable insights. A.S. attributed over $5.7 million in savings from the AI system.

Claims processing through Computer Vision technology.

Tokio Marine uses an AI-based CV technology to expedite the motor claims process in Japan. AI image recognition allows insurers to evaluate the damage to a vehicle.

The app also shares repair method recommendations and guides the claim process to ensure each claim is processed and settled as quickly as possible.

  1. Every insurance provider must become a part of the insurance ecosystem.

We are in a world of growing connected devices. McKinsey report suggests there will be about a trillion devices by 2025 that will connect and share data with interoperable standards. 

Ecosystems that will enable this data sharing are already shaping up. 

One such upcoming ecosystem is NDHM, now called ABHA. Right now, the focus of this ecosystem is on seamless data exchange between health facilities, and it is just a matter of time when this will be extended to insurance as well.

Another ecosystem that is fast around the corner is that of connected devices (medical/non-medicals/cars, fitness trackers, smart home gadgets, etc.). Data collected from these devices not only will enable insurers to create innovative products but also help in processing claims without any friction. 

Creating a frictionless Gen Z experience will require insurers to be part of these or at least hook into these ecosystems. Technology will act as an enabler in doing so. 

Summing Up

Building a great Gen Z experience on the foundations of data will need long-term conviction, patience and continuous analysis of user behavior.

Moral of the story is: Smell the cheese often so you know when it is getting old.

We should not be expecting things to remain as they were in the past. A keen eye for the data will help us be nimble and be a step ahead in meeting customer expectations.

If you’re interested in learning about next-gen technologies and how your business can make use of AI, we would love to speak with you. You can reach out to us at hello@mantralabsglobal.com

Cancel

Knowledge thats worth delivered in your inbox

Why Netflix Broke Itself: Was It Success Rewritten Through Platform Engineering?

By :

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.

Source: getport.io

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.

Cancel

Knowledge thats worth delivered in your inbox

Loading More Posts ...
Go Top
ml floating chatbot