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5 AI Trends Reshaping the Insurance Sector in 2019

NewVantage Partners Executive Survey 2019 report states- 92% of the C-Level Executives are increasing their pace of investment in big data and AI. Artificial Intelligence brings forth revolutionary benefits to enterprises like personalization, automating customer interactions, real-time assistance, and much more.

Here are 5 flourishing artificial intelligence trends in insurance.

Infographic for 5 AI trends in Insurance

#1 Data from Smart Devices

Smart devices like fitness bands, home assistants, smartwatches, etc. are meteorically becoming integral to our lifestyle. Smart clothing and medical devices are soon going to join the bandwagon.

The insurance sector can dive into the data generated by these smart devices to better understand their user preferences. This data can further help insurers create new and more personalized product categories. 

#2 UAVs for Extreme Surveillance

AI-driven unmanned aerial vehicles (UAV), also known as drones can examine sites, which are otherwise extreme for humans to visit. Using such technologies for geological surveys can make the underwriting process more accurate. Also, deploying drones and robots can revamp insurance risk management strategies. 

“It is estimated that by 2025 the number of autonomous vehicles will increase by 25%”

Source: doi.gov

#3 Channelized Data Sharing

Everyone needs data. Every industry is thriving to provide personalized products and services to its customers. Thus, one can expect private and public entities collaborating to create common platforms for data sharing. 

The data-sharing platforms are GDPR-compliant and adhere to a common cybersecurity framework. Tech giants like Google, Amazon, and Apple have already sailed into this venture. They are able to bond with the lifestyle of users through cloud connectivity and smart devices and wearables. Technology can track instances of customers’ life. Guided data sharing can enable insurance companies to provide real-time assistance to their customers.

#4 Evolution of Cognitive Technologies

Cognition is an important aspect of Artificial Intelligence. Cognitive technologies in AI mimics how the human brain works. The recent improvements in technology can provide a better framework for processing humongous data, specifically gained from active insurance products tied to definite individuals.

With cognitive technologies, carriers can constantly learn and adapt to the world around consumers. This can enable insurance companies to not bring new product categories and engagement techniques but also respond to changing underlying risks in real-time.

#5 Blockchains or Distributed Ledgers

Breaking the traditional barriers of silos and centralization, 2019 is leaping towards the combination of the best of AI and blockchain for businesses.

For example, Smart contracts can automatically determine whether an asset can be transferred to a nominee or back to the source, or a combination of both. Blockchain can also simplify claims management, reinsurance, and underwriting.

Here’s more about how distributed ledgers can accelerate insurance workflows.

Well, the benefits of blockchain are not limited to large-scale insurance companies. Any InsurTech or FinTech firm or even e-commerce marketplaces can use blockchain to distribute micro insurances. The following infographic illustrates the projects successfully harnessing AI and blockchain.

Source: LiveTiles

We help startups and enterprises, build & scale AI-driven products and solutions for last-mile environments. Reach out to us on hello@mantralabsglobal.com to learn more.

Contributing Authors: Nidhi Agrawal (Content Writer @Mantra Labs)

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Platform Engineering: Accelerating Development and Deployment

The software development landscape is evolving rapidly, demanding unprecedented levels of speed, quality, and efficiency. To keep pace, organizations are turning to platform engineering. This innovative approach empowers development teams by providing a self-service platform that automates and streamlines infrastructure provisioning, deployment pipelines, and security. By bridging the gap between development and operations, platform engineering fosters standardization, and collaboration, accelerates time-to-market, and ensures the delivery of secure and high-quality software products. Let’s dive into how platform engineering can revolutionize your software delivery lifecycle.

The Rise of Platform Engineering

The rise of DevOps marked a significant shift in software development, bringing together development and operations teams for faster and more reliable deployments. As the complexity of applications and infrastructure grew, DevOps teams often found themselves overwhelmed with managing both code and infrastructure.

Platform engineering offers a solution by creating a dedicated team focused on building and maintaining a self-service platform for application development. By standardizing tools and processes, it reduces cognitive overload, improves efficiency, and accelerates time-to-market.  

Platform engineers are the architects of the developer experience. They curate a set of tools and best practices, such as Kubernetes, Jenkins, Terraform, and cloud platforms, to create a self-service environment. This empowers developers to innovate while ensuring adherence to security and compliance standards.

Role of DevOps and Cloud Engineers

Platform engineering reshapes the traditional development landscape. While platform teams focus on building and managing self-service infrastructure, application teams handle the development of software. To bridge this gap and optimize workflows, DevOps engineers become essential on both sides.

Platform and cloud engineering are distinct but complementary disciplines. Cloud engineers are the architects of cloud infrastructure, managing services, migrations, and cost optimization. On the other hand, platform engineers build upon this foundation, crafting internal developer platforms that abstract away cloud complexity.

Key Features of Platform Engineering:

Let’s dissect the core features that make platform engineering a game-changer for software development:

Abstraction and User-Friendly Platforms: 

An internal developer platform (IDP) is a one-stop shop for developers. This platform provides a user-friendly interface that abstracts away the complexities of the underlying infrastructure. Developers can focus on their core strength – building great applications – instead of wrestling with arcane tools. 

But it gets better. Platform engineering empowers teams through self-service capabilities.This not only reduces dependency on other teams but also accelerates workflows and boosts overall developer productivity.

Collaboration and Standardization

Close collaboration with application teams helps identify bottlenecks and smooth integration and fosters a trust-based environment where communication flows freely.

Standardization takes center stage here. Equipping teams with a consistent set of tools for automation, deployment, and secret management ensures consistency and security. 

Identifying the Current State

Before building a platform, it’s crucial to understand the existing technology landscape used by product teams. This involves performing a thorough audit of the tools currently in use, analyzing how teams leverage them, and identifying gaps where new solutions are needed. This ensures the platform we build addresses real-world needs effectively.

Security

Platform engineering prioritizes security by implementing mechanisms for managing secrets such as encrypted storage solutions. The platform adheres to industry best practices, including regular security audits, continuous vulnerability monitoring, and enforcing strict access controls. This relentless vigilance ensures all tools and processes are secure and compliant.

The Platform Engineer’s Toolkit For Building Better Software Delivery Pipelines

Platform engineering is all about streamlining and automating critical processes to empower your development teams. But how exactly does it achieve this? Let’s explore the essential tools that platform engineers rely on:

Building Automation Powerhouses:

Infrastructure as Code (IaC):

CI/CD Pipelines:

Tools like Jenkins and GitLab CI/CD are essential for automating testing and deployment processes, ensuring applications are built, tested, and delivered with speed and reliability.

Maintaining Observability:

Monitoring and Alerting:

Prometheus and Grafana is a powerful duo that provides comprehensive monitoring capabilities. Prometheus scrapes applications for valuable metrics, while Grafana transforms this data into easy-to-understand visualizations for troubleshooting and performance analysis.

All-in-one Monitoring Solutions:

Tools like New Relic and Datadog offer a broader feature set, including application performance monitoring (APM), log management, and real-time analytics. These platforms help teams to identify and resolve issues before they impact users proactively.

Site Reliability Tools To Ensure High Availability and Scalability:

Container Orchestration:

Kubernetes orchestrates and manages container deployments, guaranteeing high availability and seamless scaling for your applications.

Log Management and Analysis:

The ELK Stack (Elasticsearch, Logstash, Kibana) is the go-to tool for log aggregation and analysis. It provides valuable insights into system behavior and performance, allowing teams to maintain consistent and reliable operations.

Managing Infrastructure

Secret Management:

HashiCorp Vault protects secretes, centralizes, and manages sensitive data like passwords and API keys, ensuring security and compliance within your infrastructure.

Cloud Resource Management:

Tools like AWS CloudFormation and Azure Resource Manager streamline cloud deployments. They automate the creation and management of cloud resources, keeping your infrastructure scalable, secure, and easy to manage. These tools collectively ensure that platform engineering can handle automation scripts, monitor applications, maintain site reliability, and manage infrastructure smoothly.

The Future is AI-Powered:

The platform engineering landscape is constantly evolving, and AI is rapidly transforming how we build and manage software delivery pipelines. The tools like Terraform, Kubecost, Jenkins X, and New Relic AI facilitate AI capabilities like:

  • Enhance security
  • Predict infrastructure requirements
  • Optimize resource security 
  • Predictive maintenance
  • Optimize monitoring process and cost

Conclusion

Platform engineering is becoming the cornerstone of modern software development. Gartner estimates that by 2026, 80% of development companies will have internal platform services and teams to improve development efficiency. This surge underscores the critical role platform engineering plays in accelerating software delivery and gaining a competitive edge.

With a strong foundation in platform engineering, organizations can achieve greater agility, scalability, and efficiency in the ever-changing software landscape. Are you ready to embark on your platform engineering journey?

Building a robust platform requires careful planning, collaboration, and a deep understanding of your team’s needs. At Mantra Labs, we can help you accelerate your software delivery. Connect with us to know more. 

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