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InsurTech: 5 benefits of technologies in Insurance Sector

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InsurTech is a buzzword nowadays where a variety of technologies are set to transform the traditional insurance industry. In the last two years, insurers have already transformed themselves digitally to offer convenience, security, choice, and a seamless experience to their customers.

Accenture estimates that insurance companies can increase their annual profitability by 20% with the right investment in the technology.

Internet of Things (IoT), telematics, drones, the blockchain, smart contracts, and artificial intelligence (AI) are providing new ways to measure, control, engage customers, reduce cost, improve efficiency and increase customer experience.

Here are five ways Insurers can stay ahead in the market and successfully fulfill high customer expectations. 

1. Lower Insurance rates:

 – Fitness apps or wearable devices:

Staying fit has many perks. Some of the fitness apps like Wysa and wearable devices help maintain weight, and food habits and boost energy and mood. And most importantly they can help save a huge amount of expenses related to health insurance costs. Numerous insurance providers have tapped into wearable devices to keep motivating their customers to stay fit and healthy and offer them discounts and benefits based on fitness levels.

– Self Driving car:

Self Driving cars can help in reducing the chances of accidents and lower life insurance rates. Since road deaths are a significant percentage of deaths in the entire world, any slight downward change will ultimately lead to lower deaths and hence life insurance claims.

2. Fraud Prevention:

Insurance fraud costs companies billions of dollars per year across the globe. Insurance companies should establish a technology framework, tap into advanced automation and analytics, and take steps to prevent it.

– Digital Signature:

Digital signature technology is without a doubt lowering fake insurance account activation and hence a fraud. For example, a digital signature can prevent fraud- insurance purchased after the accident can be brought down with digital signatures verifying the actual date.

– Data analytics:

The technology involves data mining tools and quantitive analysis. Data analytics can be applied to detect fraud. Predictive analytics is useful to improve the fraud detection process, helping prevent claims payouts. Analytics on claims and fraud transactions helps enhance risk management.

3. Lower underwriting cost:

–IoT

According to IoT Analytics, the global number of connected IoT devices is likely to grow at 9%, with 12.3 billion active endpoints. By 2025, there will likely be more than 27 billion IoT connections, which will have a significant impact on the availability of real-time information that insurers can use for better pricing/underwriting. Drones are satellites on steroids at least as far as underwriting is concerned. Satellites have dramatically changed how home insurance policies are written due to fire. Everything can be captured via drone footage even the houses that get covered behind the trees. Captured data can be used for underwriting purposes.

4. Billing efficiency:

Billing systems are not only integrated but now can accept varied forms of payments allowing ultimate flexibility to the customer and thereby making the billing systems efficient. The automated systems inform and remind customers of approaching due dates for premiums thereby lowering unintentional defaults.

Digital wallet has become one of the most widely used platforms for payment systems. Insurance companies are leveraging payment gateways like Google Play to sell insurance to users. Last year, SBI General Health Insurance launched Arogya Sanjeevani on Google Pay Spot to offer standard coverage at affordable premiums and improve the penetration of health insurance in the country.

5. Specialized insurance:

Each type of insurance is different from the other and the factors that are suited to one are not suited to the other. This requires the insurance agents to have specialized knowledge and the internet helps. however, Machine learning is vitally important here. It has the capability to learn and analyze billions of patterns and identify suitable underwriting clauses as well as identify specific customized plans for the customers based on the data provided. This can change the customer perception of the insurance company and provide an engaged customer who is likely to stay longer. 

Dinghy, is a pay-by-the-second insurance provider that customizes coverage for freelancers and businesses where customers may switch their policies on and off as needed without any upfront premiums, interest, credit checks, or fees. 

6.  Smart and Faster Claim Processing and Settlement: 

–AI-Powered Chatbots:

Claim settlement has been one of the pressing issues in insurance. With intense competition looming in the market, delay in the claim settlement gives a bad experience to the customer who prefers to switch to another brand. Insurance providers worldwide have been investing in AI-powered insurance chatbots to enhance customer experience. Metromile can validate 70% to 80% of claims instantly using AVA, an app based-claims assistant.

7. Data-driven pricing

–Telematics:

Innovation has become one of the top priorities for insurers today due to rapid change in customer demand. The usage-based insurance market is projected to hit over $190 billion by 2026, telematics is allowing carriers to capture user data and create personalized usage-based insurance products. 

For example, auto insurance was based on a pay-as-you-drive model where customers use to pay a premium based on the distance covered. But with technological innovation, insurers are working on a pay-how-you-drive model where customers can get discounts based on their driving skills. 

Rise in demand for innovative solutions, intelligent experiences, and speedier processes has led to technological disruption in the insurance industry. According to  IDC, IT spending in the insurance industry will increase globally at a CAGR of 6.0% by 2024, touching $135 billion. With continuous investment in technology, insurers are working on improving customer experience and operational efficiency to maximize profitability in the long run.

Thanks you Scott W Johnson, owner at WholeVsTermLifeInsurance.com for providing your valuable information on how technologies are helping Insurance industry.

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Smart Manufacturing Dashboards: A Real-Time Guide for Data-Driven Ops

Smart Manufacturing starts with real-time visibility.

Manufacturing companies today generate data by the second through sensors, machines, ERP systems, and MES platforms. But without real-time insights, even the most advanced production lines are essentially flying blind.

Manufacturers are implementing real-time dashboards that serve as control towers for their daily operations, enabling them to shift from reactive to proactive decision-making. These tools are essential to the evolution of Smart Manufacturing, where connected systems, automation, and intelligent analytics come together to drive measurable impact.

Data is available, but what’s missing is timely action.

For many plant leaders and COOs, one challenge persists: operational data is dispersed throughout systems, delayed, or hidden in spreadsheets. And this delay turns into a liability.

Real-time dashboards help uncover critical answers:

  • What caused downtime during last night’s shift?
  • Was there a delay in maintenance response?
  • Did a specific inventory threshold trigger a quality issue?

By converting raw inputs into real-time manufacturing analytics, dashboards make operational intelligence accessible to operators, supervisors, and leadership alike, enabling teams to anticipate problems rather than react to them.

1. Why Static Reports Fall Short

  • Reports often arrive late—after downtime, delays, or defects have occurred.
  • Disconnected data across ERP, MES, and sensors limits cross-functional insights.
  • Static formats lack embedded logic for proactive decision support.

2. What Real-Time Dashboards Enable

Line performance and downtime trends
Track OEE in real time and identify underperforming lines.

Predictive maintenance alerts
Utilize historical and sensor data to identify potential part failures in advance.

Inventory heat maps & reorder thresholds
Anticipate stockouts or overstocks based on dynamic reorder points.

Quality metrics linked to operator actions
Isolate shifts or procedures correlated with spikes in defects or rework.

These insights allow production teams to drive day-to-day operations in line with Smart Manufacturing principles.

3. Dashboards That Drive Action

Role-based dashboards
Dashboards can be configured for machine operators, shift supervisors, and plant managers, each with a tailored view of KPIs.

Embedded alerts and nudges
Real-time prompts, like “Line 4 below efficiency threshold for 15+ minutes,” reduce response times and minimize disruptions.

Cross-functional drill-downs
Teams can identify root causes more quickly because users can move from plant-wide overviews to detailed machine-level data in seconds.

4. What Powers These Dashboards

Data lakehouse integration
Unified access to ERP, MES, IoT sensor, and QA systems—ensuring reliable and timely manufacturing analytics.

ETL pipelines
Real-time data ingestion from high-frequency sources with minimal latency.

Visualization tools
Custom builds using Power BI, or customized solutions designed for frontline usability and operational impact.

Smart Manufacturing in Action: Reducing Market Response Time from 48 Hours to 30 Minutes

Mantra Labs partnered with a North American die-casting manufacturer to unify its operational data into a real-time dashboard. Fragmented data, manual reporting, delayed pricing decisions, and inconsistent data quality hindered operational efficiency and strategic decision-making.

Tech Enablement:

  • Centralized Data Hub with real-time access to critical business insights.
  • Automated report generation with data ingestion and processing.
  • Accurate price modeling with real-time visibility into metal price trends, cost impacts, and customer-specific pricing scenarios. 
  • Proactive market analysis with intuitive Power BI dashboards and reports.

Business Outcomes:

  • Faster response to machine alerts
  • Quality incidents traced to specific operator workflows
  • 4X faster access to insights led to improved inventory optimization.

As this case shows, real-time dashboards are not just operational tools—they’re strategic enablers. 

(Learn More: Powering the Future of Metal Manufacturing with Data Engineering)

Key Takeaways: Smart Manufacturing Dashboards at a Glance

AspectWhat You Should Know
1. Why Static Reports Fall ShortDelayed insights after issues occur
Disconnected systems (ERP, MES, sensors)
No real-time alerts or embedded decision logic
2. What Real-Time Dashboards EnableTrack OEE and downtime in real-time
Predictive maintenance using sensor data
Dynamic inventory heat maps
Quality linked to operators
3. Dashboards That Drive ActionRole-based views (operator to CEO)
Embedded alerts like “Line 4 down for 15+ mins”
Drilldowns from plant-level to machine-level
4. What Powers These DashboardsUnified Data Lakehouse (ERP + IoT + MES)
Real-time ETL pipelines
Power BI or custom dashboards built for frontline usability

Conclusion

Smart Manufacturing dashboards aren’t just analytics tools—they’re productivity engines. Dashboards that deliver real-time insight empower frontline teams to make faster, better decisions—whether it’s adjusting production schedules, triggering preventive maintenance, or responding to inventory fluctuations.

Explore how Mantra Labs can help you unlock operations intelligence that’s actually usable.

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