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Autonomous Vehicle Insurance: The Present and Near Future

We’re about to witness the evolution of autonomous vehicles from Level 0 to Level 2. While Level 0 is completely human-driven; Level 1 vehicles can control braking and parallel parking themselves. Level 2 vehicles can operate automatically, but with a human ready to control exceptional situations.

The success of self-driving cars depends solely on the safety it brings to transportation. With increased safety, will we even need insurance for autonomous vehicles?

Perhaps, the traditional insurance policies might face a setback. But, autonomous vehicles will certainly open new avenues for innovative insurance products.

The Stevens Institute of Technology predicts that there would be over 23 million fully autonomous vehicles by 2035 in the US alone. 

To stay competitive with the changing dynamics of auto insurance, insurers need to address new risks. But before, let’s take a look at potential risks in the autonomous vehicle insurance sector.

Autonomous vehicle insurance: the evolution of autonomous cars from Level 0 to Level 5

Potential Impact of ‘Autonomous Vehicles’ Revolution

The shift to autonomous vehicles tends to bring dramatic changes in auto insurance premiums.  

Instead of individual policies, researchers foresee insurance policies turning towards original equipment manufacturers (OEMs) and service providers such as ride-sharing companies. The new auto insurance products would be an outcome of the following transportation changes.

New Road Regulations

With autonomous vehicles on the roads, safety regulations are prone to change. For instance, the US National Highway Traffic Safety Administration intends to reconsider its current safety standards to accommodate AVs in existing transportation. But, this reformation will take the presence of human drivers into account.

Increased Safety and Reduced Claims

With increased safety and reduced accident claims, the revenues from traditional premium policies might decline.  

Insurers often follow a “no-fault” system to lower auto insurance costs by taking small claims out of the courts. For minor injuries, insurers compensate their policyholders regardless of who was at fault in the accident. 

However, fender-benders would be more than it is with autonomous vehicles. Also, blockchain in insurance would become integral to investigate the root cause of the accident. And, of course, there won’t be much scope for lenient “no-fault” policies. 

Change in Insurance Liability

Traditional liability insurance pays for the policyholder’s legal responsibility to others for bodily injury or property damage. With autonomous vehicles, the liability is going to shift towards OEMs, suppliers, or car-rental service providers.

Underwriting?

Currently, automakers must adhere to around 75 safety standards. This underwriting considers that a licensed driver will control the vehicle. The safety standards are going to change with more AVs on roads.

The present-day premium is high for a handful of autonomous vehicles because of insufficient data with underwriters and actuaries. However, chances are, major OEMs will cover the insurance premiums in the vehicle cost. 

For instance, Tesla, one of the pioneers of autonomous vehicles, provides auto insurance at 30% lower rates than other insurance providers. Tesla having a better understanding of its vehicles’ technology and repair costs, believes can provide low-cost insurance. This is also a threat to insurance carrier fees.

Scope for New Autonomous Vehicle Insurance Products

Accenture estimates that autonomous vehicles will generate at least $81 billion in new insurance revenues in the US between 2020 and 2025. It also foresees opportunities for insurers in cybersecurity, product, and infrastructure landscapes. Let’s take a look at new auto insurance avenues. 

Cyber Security

While AVs ensure safety, there are unidentified cybersecurity threats. Vehicles fueled by IoT technology deal with comprehensive telematics data. Capturing every moment of the user proposes risks like identity theft, privacy invasion, misuse of personal information, and attacks from ransomware. According to the Center for Strategic and International Studies and McAfee, globally cybercrimes cost around $600 billion annually. The shared data from autonomous vehicles bring the financial sector at risk.

On the other hand, monitoring the performance of vehicles and the driver’s behavior behind the wheel can reduce claim investigation turn around time. 

Therefore, future insurance products will also focus on moral and financial threats to passengers.

Product Liability

The product liability insurance might shift from automotive to sensors and algorithms behind the autonomous vehicle. The OEMs will be also liable for communication or Internet connection failure along with machinery and software failures.

Insurance Against Existing Infrastructure

It will take more than 30 years for autonomous vehicles to completely dominate transportation. The upcoming insurance products will take existing infrastructure into account. For example, AVs need insurance if it damages due to puddles or potholes on the road.

Also, car ownership tends to decline with rental and pay-as-you-use models. This opens a fleet-level opportunity for insurers for driverless cars.

Source: Accenture X Stevens Institute of Technology “Insuring Autonomous Vehicles” report

Insurers need to adapt to the rapid technological advancements. Cloud-based insurance workflow platforms or IaaS (Insurance as a Service) models help in achieving operational gains in the entire insurance value chain. 

Concluding Remarks

AVs are going to dominate the world’s highway because of improved safety and convenience. Companies can leverage this opportunity to introduce innovative autonomous vehicle insurance products. 

Growing IoT is blurring the fine-line between different verticals of insurance. To stay competitive, insurers should also indulge in creating new distribution channels and partnerships with OEMs and technology service providers.

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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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