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Is Insurance Moving Up the Customer Experience Value Chain

4 minutes, 36 seconds read

The insurance industry has been thriving to establish a strong connection with customers. The challenge is, however, intense with digital disruption and new avenues for customer risks. Insurance companies are catching the pace of the technological revolution and harnessing technology to bring more relevant products to the customers. While ‘customer satisfaction’ lies at the centre of businesses today, is insurance moving up the customer experience value chain? Let’s see.

Insurance Now and a Decade Ago

Traditionally, a customer would call the insurance company during instances of claims. The customer would hear from the company only when the policy renewal time is approaching. This indicates the need for an ice-breaker in the insurance-customer relationship.

A decade ago, insurers intended to harmonize customer interactions — the touchpoints. Normally, any insurance company can have 4-7 customer touchpoints. Even though individual touchpoints are performing, the overall experience for a customer might not be satisfactory.

Is Insurance Moving Up the Customer Experience Value Chain Satisfaction-touchpoints-X-customer-journey

Customer satisfaction depends on five factors: interaction; price; policy offerings; billing & payment; and claims. However, to train the entire organization to see the interactions with customers’ eyes is still a challenge. It’s not possible to revamp the entire system overnight, but identifying the pain-points and acting upon them can surely move insurers up the ‘experience’ value chain.

For instance, the year 2014-15 witnessed one of the hefty market slowdowns in the automobile sector. Despite this, the millennials expressed an increase in satisfaction for their car-insurance services. The main reason for the increased satisfaction in the customer experience value chain was measurably improved interactions. 

Resource: “Improved Interactions Drive Gen Y Increase in Auto Insurance Satisfaction.”

Addressing the fact that more touchpoints lead to more operational challenges and time to deliver results; insurers prototyped single-point-of-contact models during 2015-16. Here, a personalized agent would take care of the customer interactions. The results were profound, and this step is a milestone in defining the customer journey as a whole. McKinsey’s research finds that customer journeys are more strongly correlated with business outcomes than touchpoints.

Also read: Customer Journey is the New Product!

Today, organizations are leveraging technologies to speed-up processes like policy distribution, underwriting, and claim settlements. For instance, USAA (The United Services Automobile Association) is developing machine learning models to instantly predict vehicle damage from digital images and offer claim estimates.

Recent Developments in Insurance

According to Accenture, 76% of customers would switch providers for more personalized service and tailored product offerings. Insurers are, therefore, not only concerned about “what my customers want,” but also – “how my customers want.” 

Organizations are using technology to provide tailored solutions to customers specific to their requirements. Artificial intelligence (AI), Machine Learning (ML), IoT, Blockchain, and Data analytics are strengthening the insurtech sector. 

Carriers are using AI and ML to improve underwriting for mitigating risks. For example, Cape Analytics uses AI and geospatial imagery to provide instant property intelligence. Insurers can, therefore, accurately assess a property’s risk and value.

As mentioned before, claim settlement is one of the five major factors influencing customer satisfaction in insurance. Insurers are leveraging AI and cloud technology to settle claims in minutes or even less. For example, ICICI Lombard uses Cognitive Computing, Intelligent Character Recognition (ICR), and Optical Character Recognition (OCR) to automate the claim settlement process. Similarly for health insurance, ICICI Lombard is covering medical procedures like Cataract, Maternity, Appendicitis, Hemodialysis, and Hysterectomy for app-based claim settlement.

Also read – how AI can settle claims in 5 minutes!

Insurance companies are also automating workflows inline with their existing processes. It is helping insurers to bridge the technology gap between Gen X, Millennials, and Gen Z customers. Efficient insurance workflow automation solutions are trained to decipher industry-specific jargon and at the same time, interact with the user using NLP (Natural Language Processing) techniques.

Another remarkable advancement in insurance CRM is the adoption of chatbots. It is a viable solution to serve multiple customers concurrently. For example, Religare, a leading insurer was able to increase customer interactions by 10x through chatbots.

Religare Chatbot

The present time also sees customers’ growing intent towards micro policies, which serve a single purpose instead of an all-encompassing insurance scheme. Technology is also helping to distribute micro policies in scale with almost zero upfront costs. For example, Gramcover, an Indian microinsurance startup uses direct-document uploading and processing for distributing policies in rural areas.

What Customers Say?

The World InsurTech Report 2019 indicates that less than 25% of business customers and 15% retail policyholders believe they’re covered against all emerging risks. However, 28% of individual customers are amenable to share additional data for more comprehensive services. Also, 15% of customers are willing to pay an additional fee for relevant services

The takeaway —  ‘relevance’ is the key to today’s customers. Insurance companies can leverage this opportunity to provide products related to emerging threats like identity theft, privacy invasion, misuse of personal information, and attacks from ransomware. 

In 2018, about 30% of customers selected their insurer in a single day, according to a survey from the Insurance Information Institute. Through creating exceptional customer experiences, insurers can set themselves apart from their competitors. And the answer to ‘how’ to create this exceptional experience lies in focusing on the journey more than the customer touchpoints.

The customer interaction preferences will keep on changing. Today, millennials prefer to interact with insurers via digital self-service. Tomorrow, Gen Z might want complete automation, i.e. no interaction at all. How fast the insurance industry adapts to the changing preferences will determine the level of satisfaction in the customer experience value chain.

We provide insurtech solutions for business-specific challenges. Feel free to drop us a line at hello@mantralabsglobal.com, illustrating your requirements.

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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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