InsurTech: 5 benefits of technologies in Insurance Sector

Published on Nov 13, 2017

Updated on Jun 9, 2022

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.

Not too long ago, storing data meant dedicating an entire room to massive CPUs. Then came the era of personal computers, followed by external hard drives and USB sticks. Now, storage has become practically invisible, floating somewhere between data centers and, well, the clouds—probably the ones in the sky. Cloud computing continues to evolve, As cloud computing evolves, optimizing costs without sacrificing performance has become a real concern. How can organizations truly future-proof their cloud strategy while reducing costs? Let’s explore new-age cloud optimization strategies in 2025 designed for maximum performance and cost efficiency.

Smarter Cloud Strategies: Cutting Costs While Boosting Performance

1. AI-Driven Cost Prediction and Auto-Optimization

When AI is doing everything else, why not let it take charge of cloud cost optimization too? Predictive analytics powered by AI can analyze usage trends and automatically scale resources before traffic spikes, preventing unnecessary over-provisioning. Cloud optimization tools like AWS Compute Optimizer and Google’s Active Assist are early versions of this trend.

How it Works: AI tools analyze real-time workload data and predict future cloud resource needs, automating provisioning and scaling decisions to minimize waste while maintaining performance.
Use case: Netflix optimizes cloud costs by using AI-driven auto-scaling to dynamically allocate resources based on streaming demand, reducing unnecessary expenditure while ensuring a smooth user experience.

2. Serverless and Function-as-a-Service (FaaS) Evolution

That seamless experience where everything just works the moment you need it—serverless computing is making cloud management feel exactly like that. Serverless computing eliminates idle resources, cutting down costs while boosting cloud performance. You only pay for the execution time of functions, making it a cost-effective cloud optimization technique.

How it works: Serverless computing platforms like AWS Lambda, Google Cloud Functions, and Azure Functions execute event-driven workloads, ensuring efficient cloud resource utilization while eliminating the need for constant infrastructure management.
Use case: Coca-Cola leveraged AWS Lambda for its vending machines, reducing backend infrastructure costs and improving operational efficiency by scaling automatically with demand.

3. Decentralized Cloud Computing: Edge Computing for Cost Reduction

Why send all your data to the cloud when it can be processed right where it’s generated? Edge computing reduces data transfer costs and latency by handling workloads closer to the source. By distributing computing power across multiple edge nodes, companies can avoid expensive, centralized cloud processing and minimize data egress fees.

How it works: Companies deploy micro data centers and AI-powered edge devices to analyze data closer to the source, reducing dependency on cloud bandwidth and lowering operational costs.
Use case: Retail giant Walmart leverages edge computing to process in-store data locally, reducing latency in inventory management and enhancing customer experience while cutting cloud expenses.

4. Cloud Optimization with FinOps Culture

FinOps (Cloud Financial Operations) is a cloud cost management practice that enables organizations to optimize cloud costs while maintaining operational efficiency. By fostering collaboration between finance, operations, and engineering teams, FinOps ensures cloud investments align with business goals, improving ROI and reducing unnecessary expenses.

How it works: Companies implement FinOps platforms like Apptio Cloudability and CloudHealth to gain real-time insights, automate cost optimization, and enforce financial accountability across cloud operations.
Use case: Early adopters of FinOps were Adobe, which leveraged it to analyze cloud spending patterns and dynamically allocate resources, leading to significant cost savings while maintaining application performance.

5. Storage Tiering with Intelligent Data Lifecycle Management

Not all data needs a VIP seat in high-performance storage. Intelligent data lifecycle management ensures frequently accessed data stays hot, while infrequently used data moves to cost-effective storage. Cloud-adjacent storage, where data is stored closer to compute resources but outside the primary cloud, is gaining traction as a cost-efficient alternative. By reducing egress fees and optimizing storage tiers, businesses can significantly cut expenses while maintaining performance.

How it’s being done: Companies use intelligent storage optimization tools like AWS S3 Intelligent-Tiering, Google Cloud Storage’s Autoclass, and cloud-adjacent storage solutions from providers like Equinix and Wasabi to reduce storage and data transfer costs.
Use case: Dropbox optimizes cloud storage costs by using multi-tiered storage systems, moving less-accessed files to cost-efficient storage while keeping frequently accessed data on high-speed servers.

6. Quantum Cloud Computing: The Future-Proof Cost Gamechanger

Quantum computing sounds like sci-fi, but cloud providers like AWS Braket and Google Quantum AI are already offering early-stage access. While still evolving, quantum cloud computing has the potential to process vast datasets at lightning speed, dramatically cutting costs for complex computations. By solving problems that traditional computers take days or weeks to process, quantum computing reduces the need for excessive computing resources, slashing operational costs.

How it works: Cloud providers integrate quantum computing services with existing cloud infrastructure, allowing businesses to test and run quantum algorithms for complex problem-solving without massive upfront investments.
Use case: Daimler AG leverages quantum computing to optimize battery materials research, reducing R&D costs and accelerating EV development.

7. Sustainable Cloud Optimization: Green Computing Meets Cost Efficiency

Running workloads when renewable energy is at its peak isn’t just good for the planet—it’s good for your budget too. Sustainable cloud computing aligns operations with renewable energy cycles, reducing reliance on non-renewable sources and lowering overall operational costs.

How it works: Companies use carbon-aware cloud scheduling tools like Microsoft’s Emissions Impact Dashboard to track energy consumption and optimize workload placement based on sustainability goals.
Use case: Google Cloud shifts workloads to data centers powered by renewable energy during peak production hours, reducing carbon footprint and lowering energy expenses.

The Next Frontier: Where Cloud Optimization is Headed

Cloud optimization in 2025 isn’t just about playing by the old rules. It’s about reimagining the game entirely. With AI-driven automation, serverless computing, edge computing, FinOps, quantum advancements, and sustainable cloud practices, businesses can achieve cost savings and high cloud performance like never before.

Organizations that embrace these innovations will not only optimize their cloud spend but also gain a competitive edge through improved efficiency, agility, and sustainability. The future of cloud computing in 2025 isn’t just about cost-cutting—it’s about making smarter, more strategic cloud investments.

At Mantra Labs, we specialize in AI-driven cloud solutions, helping businesses optimize cloud costs, improve performance, and stay ahead in an ever-evolving digital landscape. Let’s build a smarter, more cost-efficient cloud strategy together. Get in touch with us today!

Are you ready to make your cloud strategy smarter, cost-efficient, and future-ready with AI-driven, serverless, and sustainable innovations?