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How Technology is Transforming Insurance Distribution Channels

4 minutes, 31 seconds read

‘Insuring’ has always been a mundane and complicated subject for businesses. Distribution channels allow customers to access and purchase products efficiently. According to JM Financial, online insurance sales for new business are fast catching up and are likely to grow at a CAGR of 13 percent to become a $37 billion break by 2025.

Each distribution channel requires different resources to be effective and impact the pricing structure. The type of insurance business model determines its structure, strategy and placement in the market.

Take, for instance, India. The market size of the online insurance business in India is currently $15 billion, but the overall insurance penetration rate is just 3.7% (Statista, 2018). 

The regions where insurance penetration is low poses an immense potential for the digital premium market. Insurers can leverage the following distribution channels to undermine the profound potential.

1. Self-directed or Direct Distribution Channel

Through Self-directed or direct distribution channels, insurers can reach out to the customers without shelling out commission for any middle man. With an increase in the population of tech-savvy customers, the ready availability or online channel of advice or transaction capabilities is the need of the hour. 

Online channels, websites, social media platforms, e-commerce and kiosks are some examples of the direct distribution channels in insurance. The 2017 Global Distribution and Marketing Consumer Study reveals that nearly 51% of digitally active groups of consumers (39% of all Insurance consumers) have purchased insurance through an online channel. The direct insurance distribution channel encourages self-service and independent decision making.

NLP-powered chatbots are a great way to provide a self-service portal for buying/renewing insurance policies. Leading Insurers like Religare are leveraging the direct distribution channel by integrating chatbots in different platforms like their website, mobile app, and even on third-party apps like WhatsApp.

2. Assisted Distribution

Agents and brokers are typically the key players in the insurance distribution channel, with market shares of 42% and 25% respectively. The old school face-to-face distribution channel is very much alive and is integrated with tech assisted models to ensure more leads and conversions. They mainly play a part in advising and managing complex insurance products.

agent's share in assisted insurance distribution channel

Agents, insurance brokers and reinsurance brokers remain the most recognized insurance purchase channel. The Gartner Group reports that 60% of the US GDP is sold through assisted or indirect channels. Cognitive technology is becoming a key enabler to strengthen the assisted distribution channel. PwC suggests leveraging analytics solutions (mainly predictive analytics and behavioral analytics) to increase sellers’ knowledge as well as skills.

[Related: How behavioral psychology is fixing modern insurance claims]

The technologies that are empowering learning for Insurers include augmented reality, machine learning, data analysis and NLP.

upcoming technologies in assisted distribution channel

For example, Zelros, a European AI startup, is augmenting the knowledge of sales and customer representatives through best product recommendations, advisory, and pricing based on the customer profile in real-time.

3. Affinity-based Insurance Distribution Channels

The affinity channel focuses on distributing products to a tightly-connected group of consumers with similar interests. Traditionally, the affinity-based distribution channel involved peer-to-peer networks, brokers and aggregators. While the network model remains the same, the model has become digital and tech-driven for affinity channels. And technology is playing a vital role in expanding the consumer base. The key benefits of the affinity distribution channel are-

  • Common platform for all stakeholders.
  • One-stop access to policies and claims.
  • Centralized database for insightful analysis.
API-based Insurance Model Affinity Distribution Channel

This distribution channel is also a part of B2B2C or API-based insurance business models. Here, Insurers can leverage 3rd party apps to distribute their policies. APIs or Application Programming Interfaces are lightweight programs to extend the functionality of existing apps. Travel, airbus, hotel, bank and retail are some examples of affinity-based distribution channels.

Finaccord estimates that airline companies hold a distribution share of up to 10% of the travel insurance market. The annual revenue from airline and travel insurance providers partnership may range from $1.2 billion to 1.5 billion in premiums.

[Related: 4 New Consumer-centric Business Models in Insurance, How InsurTech-Insurance Partnership Delivers New Product Innovations]

The majority of travel insurance policy sales across the globe are done through some kind of affinity partner instead of via a direct sales channel.

Jeff Rutledge, President & CEO, AIG Travel
Source: Insurance Business UK

The Bottom Line

In the countries where buying an Insurance is not mandatory, market penetration is extremely low for Insurers. Being meticulous in sales and marketing efforts and educating customers about the benefits of insurance is just not sufficient. Convenience is the key to new generation consumers. Therefore, insurers need to invest in technology and make insurance policies accessible to the new-age digital consumers through the channel of their choice. 

Michael D. Hutt and Thomas W. Speh, in their book – Business Marketing Management: B2B, suggest a six-step process to select among the most efficient insurance distribution channels-

  1. Determine the target customers.
  2. Identify and prioritize customer channel requirements by segment.
  3. Access the business’s capabilities to meet those customer requirements.
  4. Use the channel offering as a yardstick against those offered by competitors.
  5. Create a channel solution for customers’ needs.
  6. Evaluate and select the most effective among the distribution channels.

We’ve developed insurance chatbots for organizations like Religare to automate policy distribution and renewal. For your business-specific requirement, please feel free to reach us at hello@mantralabsglobal.com.

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Smart Machines & Smarter Humans: AI in the Manufacturing Industry

We have all witnessed Industrial Revolutions reshape manufacturing, not just once, but multiple times throughout history. Yet perhaps “revolution” isn’t quite the right word. These were transitions, careful orchestrations of human adaptation, and technological advancement. From hand production to machine tools, from steam power to assembly lines, each transition proved something remarkable: as machines evolved, human capabilities expanded rather than diminished.

Take the First Industrial Revolution, where the shift from manual production to machinery didn’t replace craftsmen, it transformed them into skilled machine operators. The steam engine didn’t eliminate jobs; it created entirely new categories of work. When chemical manufacturing processes emerged, they didn’t displace workers; they birthed manufacturing job roles. With each advancement, the workforce didn’t shrink—it evolved, adapted, and ultimately thrived.

Today, we’re witnessing another manufacturing transformation on factory floors worldwide. But unlike the mechanical transformations of the past, this one is digital, driven by artificial intelligence(AI) working alongside human expertise. Just as our predecessors didn’t simply survive the mechanical revolution but mastered it, today’s workforce isn’t being replaced by AI in manufacturing,  they’re becoming AI conductors, orchestrating a symphony of smart machines, industrial IoT (IIoT), and intelligent automation that amplify human productivity in ways the steam engine’s inventors could never have imagined.

Let’s explore how this new breed of human-AI collaboration is reshaping manufacturing, making work not just smarter, but fundamentally more human. 

Tools and Techniques Enhancing Workforce Productivity

1. Augmented Reality: Bringing Instructions to Life

AI-powered augmented reality (AR) is revolutionizing assembly lines, equipment, and maintenance on factory floors. Imagine a technician troubleshooting complex machinery while wearing AR glasses that overlay real-time instructions. Microsoft HoloLens merges physical environments with AI-driven digital overlays, providing immersive step-by-step guidance. Meanwhile, PTC Vuforia’s AR solutions offer comprehensive real-time guidance and expert support by visualizing machine components and manufacturing processes. Ford’s AI-driven AR applications of HoloLens have cut design errors and improved assembly efficiency, making smart manufacturing more precise and faster.

2. Vision-Based Quality Control: Flawless Production Lines

Identifying minute defects on fast-moving production lines is nearly impossible for the human eye, but AI-driven computer vision systems are revolutionizing quality control in manufacturing. Landing AI customizes AI defect detection models to identify irregularities unique to a factory’s production environment, while Cognex’s high-speed image recognition solutions achieve up to 99.9% defect detection accuracy. With these AI-powered quality control tools, manufacturers have reduced inspection time by 70%, improving the overall product quality without halting production lines.

3. Digital Twins: Simulating the Factory in Real Time

Digital twins—virtual replicas of physical assets are transforming real-time monitoring and operational efficiency. Siemens MindSphere provides a cloud-based AI platform that connects factory equipment for real-time data analytics and actionable insights. GE Digital’s Predix enables predictive maintenance by simulating different scenarios to identify potential failures before they happen. By leveraging AI-driven digital twins, industries have reported a 20% reduction in downtime, with the global digital twin market projected to grow at a CAGR of 61.3% by 2028

4. Human-Machine Interfaces: Intuitive Control Panels

Traditional control panels are being replaced by intuitive AI-powered human-machine interfaces (HMIs) which simplify machine operations and predictive maintenance. Rockwell Automation’s FactoryTalk uses AI analytics to provide real-time performance analytics, allowing operators to anticipate machine malfunctions and optimize operations. Schneider Electric’s EcoStruxure incorporates predictive analytics to simplify maintenance schedules and improve decision-making.

5. Generative AI: Crafting Smarter Factory Layouts

Generative AI is transforming factory layout planning by turning it into a data-driven process. Autodesk Fusion 360 Generative Design evaluates thousands of layout configurations to determine the best possible arrangement based on production constraints. This allows manufacturers to visualize and select the most efficient setup, which has led to a 40% improvement in space utilization and a 25% reduction in material waste. By simulating layouts, manufacturers can boost productivity, efficiency and worker safety.

6. Wearable AI Devices: Hands-Free Assistance

Wearable AI devices are becoming essential tools for enhancing worker safety and efficiency on the factory floor. DAQRI smart helmets provide workers with real-time information and alerts, while RealWear HMT-1 offers voice-controlled access to data and maintenance instructions. These AI-integrated wearable devices are transforming the way workers interact with machinery, boosting productivity by 20% and reducing machine downtime by 25%.

7. Conversational AI: Simplifying Operations with Voice Commands

Conversational AI is simplifying factory operations with natural language processing (NLP), allowing workers to request updates, check machine status, and adjust schedules using voice commands. IBM Watson Assistant and AWS AI services make these interactions seamless by providing real-time insights. Factories have seen a reduction in response time for operational queries thanks to these tools, with IBM Watson helping streamline machine monitoring and decision-making processes.

Conclusion: The Future of Manufacturing Is Here

Every industrial revolution has sparked the same fear, machines will take over. But history tells a different story. With every technological leap, humans haven’t been replaced; they’ve adapted, evolved, and found new ways to work smarter. AI is no different. It’s not here to take over; it’s here to assist, making factories faster, safer, and more productive than ever.

From AR-powered guidance to AI-driven quality control, the factory floor is no longer just about machinery, it’s about collaboration between human expertise and intelligent systems. And at Mantra Labs, we’re diving deep into this transformation, helping businesses unlock the true potential of AI in manufacturing.

Want to see how AI-powered Augmented Reality is revolutionizing the manufacturing industry? Stay tuned for our next blog, where we’ll explore how AI in AR is reshaping assembly, troubleshooting, and worker training—one digital overlay at a time.

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