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7 Chatbot Trends in Insurance 2021

5 minutes read

The chatbot market was valued at USD 17.17 billion in 2020 and is projected to reach USD 102.29 billion by 2026, which, in other words, it is a 34.75% rise in CAGR over the forecast period (2021-2026). 

“According to some estimates, by 2025 95% of all customer interactions will be powered by chatbots”, reports DuckCreek technologies on their blog. 

“Utilizing AI and machine learning, chatbots can interact with customers seamlessly, saving everyone within an organization time – and ultimately saving insurance companies money. A bot can walk a customer through a policy application or claims process, reserving human intervention for more complex cases,” the blog continues. 

Source: www.mantralabsglobal.com

As chatbots help reduce operational costs and increase customer experience for global enterprises, their market size is likely to increase gradually, thus giving an impetus to Chatbot marketing, online payments, customer service, and similar segments. 

Source: chatbotsmagazine.com 

As we head to the second half of 2021, here’s a look at some of the chatbot trends we expect to see: 

  • Customer Intelligence: 

Predictive Analytics depends on a number of statistical techniques including data mining, predictive modeling, pattern matching, and machine learning. The efficient usage of relevant techniques and algorithms for bots helps to ensure not just premium customer experience but also meeting other business requirements. Integrating advanced behavioral analytics to chatbots is now common practice for companies either as standalone software or as a built-in feature, resulting in a better customer experience.

  • Faster claims handling:

Insurance chatbots are a swift way of arriving at a resolution especially when the query requires minimal support from a human, case in point, pulling up relevant data, answering a question and also, filing a claim. A customer can just ask the bot to help them file a claim and the chatbot gets to work by scanning and pulling up the customer’s policy from the insurer’s database or backend system, ask the customer for any additional details (including a security step), and then initiate the claims filing process. 

  • Conversational AI

Conversational AI will go a long way in helping bridge knowledge gaps and lend more clarity around insurance. An AI-based assistant is the first step in responding to a customer’s queries around plans and policies, benefits and coverage, pricing, payment plans and options, and more. For Care Health Insurance, Mantra Labs built Hitee, an emotionally intelligent chatbot, who works as an entry-level customer support specialist aiding Care Health Insurance with customer queries around insurance. 

  • Video Call Support: 

The COVID-19 pandemic saw a surge in phone calls and video calls as there was an increased need to stay home. On a video call, you can see the person you’re talking to, and read their facial expressions, which is almost as good as face-to-face interaction. However, in case of a video chatbot, you aren’t talking with a human but a chatbot with a digital human avatar. Suitably dubbed ‘artificial humans’, a video chatbot has the ability to help customers through its digitally rendered human face, body, and voice.

This newfound breed of digital humankind works on a mix of machine learning and neural networks which has thus far allowed these avatars to better mimic human emotion and behavior. 

  • Local Languages and Dialects

According to Indian Languages – Defining India’s Internet, a report by KPMG, “Chat applications cater to 170 million Indian language internet users. This is expected to grow to 400 million by 2021 at a CAGR of 19%.” 

Source: Indian Languages – Defining India’s Internet, KPMG 

A multilingual chatbot allows enterprises to connect and converse with consumers across language and cultural barriers helping to enhance engagement and conversions. However, building multilingual chatbots requires more than using a language translator to process text or dialogue from English to another language. 

To make multi-language communication effective and on point, a chatbot must be trained on an end user’s culture, history, and any regional nuances. Additionally, global enterprises are also building multichannel bots that connect multiple messaging platforms or voice channels to the same project. 

  • Emotional Awareness

Picture this: You have had a tough day at work and so you want to wind down and get ready for the weekend, stress-free. However, owing to the pandemic and a continued spate of work-from-home scenarios, the usual Friday night out with friends is a far-fetched dream. What’s the next thing you turn to? Fortunately, there’s an option available for that in the form of chatbots with high emotional intelligence that captures human sentiment, emotional states and elicits positive responses during a conversation, while making sure that the person on the other side of the screen feels safe speaking to a stranger, in this case, a machine. 

Wysa, rated as one of the most innovative mental health support apps, does exactly that. You can have a normal conversation, engage in exercises to help you through anxious phases, listen to sleep sounds that calm your nerves, and it also offers an option to speak to a therapist. Wysa’s EQ also ensures that she makes timely follow-ups to ask how you’re doing and sends weekly reports as a summation of your past conversations. 

A Pew Research Center study reports that by the year 2025, AI and robotics will permeate most aspects of one’s daily life. 

  • Personalized Marketing

Gartner had previously predicted that by the year 2020, people would have more conversations with chatbots than their spouses. The chatbots of the future are not just programmed to respond to questions, but to talk and draw relevant insights from knowledge graphs and eventually, forging emotional relationships with customers. 

Sephora’s Facebook Messenger bot is a popular use case when discussing chatbot personalization. The cosmetics company built and deployed a bot to allow customers to book an appointment for an in-store takeover which resulted in a whopping 11% higher conversion rate than any other booking channels Sephora used. 

Chatbots are constantly on the rise amid the need for customers to be online 24X7. Chatbot architecture and design are fast-evolving to the level that conversational AI will become a standard customer service practice. Noteworthy tech companies are pushing themselves forward in industries like retail, banking and finance, and healthcare sectors with the development of advanced chatbots powered by artificial intelligence and machine learning.

According to linchpin.seo, “Experts believe that AI will be a major investment in customer experience for a few years. 47% of organizations are expected to implement chatbots for customer support services, and 40% are expected to adopt virtual assistants. Predictions of consumer-based services suggest that chatbots will be programmed to match human behavior, offer similar services, and improve customer service.” 

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

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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.

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