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Insurance as a service

4 minutes, 26 seconds read

The past years have seen strong traction in “as a Service” business model across several industries. The insurance industry is no different. 

The idea behind XaaS, or “as a Service” is that one can buy services from vendors on a subscription-basis – depending on their needs and requirements. It is especially beneficial to reduce time to benefit, installation costs, ensure scalability and swift upgrades. XaaS often corresponds to the availability of service on the cloud.

[Read More: Everything as a Service]

Now, 

What is Insurance as a Service?

Insurance as a Service implies that individuals or companies can buy pre-built elements of Insurance services on subscription-basis as per their needs and requirements.

How is Insurance-as-a-Service different from Sandbox?

The Sandbox approach emphasizes on experimenting and learning before finally adopting technology or systems to reduce the impact of failure. Whereas Insurance as a Service is a platform built after testing done on a wide user base and is available for users on a subscription basis. Insurers use a sandbox approach to test product-market fit before the actual release. Individuals, corporates, and even insurance companies can benefit from Insurance as a Service.
Details – Sandbox Approach in Insurance

What makes Insurance as a Service model impressive?

Insurance as a Service model requires only a little to no capital expenditure. The service infrastructure, owned by the provider, distributes the cost across users. 

After studying business cases, primarily for incumbent processes, corporates and stakeholders can test a particular service before actually investing in it. Businesses need not overhaul their core functions for integrations. A small-scale trial can be enough to adopt a specific model. In many such ways, Insurance as a service is an excellent option for incumbents, entrepreneurs, and startups.

Prerequisites

XaaS products are, in general, scalable and can be integrated across a variety of platforms without compromising customization and customer experiences. Their infrastructure relies heavily on data, analytics and contextual tools. The fundamental requirements from Insurance as a Service infrastructure are:

1. Customer analytics

Why: Advanced analytical technologies are great to get an insight about customer psychology and implement them to create related products. 

How: NLP-powered chatbots can create a transparent platform for communication with customers and dive into the functional requirements of the product.

[Related:The State of AI Chatbots in Insurance Report]

2. Personalized data

Why: This is a high-time to humanize conversations with customers and establish a real-time personalized relationship.

How: Through the omnichannel approach, it is possible to gather and unify customer data collected from various sources like social media, website, communication with agents, to name some.

3. Contextual tools

Why: To formulate products that can match customer expectations, offer convenience and empathy-based experiences.

How: Leveraging analytics, emotion AI and NLP-based technologies to analyze customers’ intent and perceptions about your brand from multiple sources (e.g. social media, forums, etc.)

How are start-ups developing models for Insurance as a Service?

As per recent InsurTech developments, start-ups are pursuing the following 3 Insurance as a Service model:

1. Full-stack

It involves an end-to-end infrastructure to deploy digital insurance. Here, a technology company can develop a platform for Insurance processes as well as licensed white-label backend. For example, Swiss startup Stonestep provides Micro-insurance as a Service by partnering with mobile network operators, retailers, and vendors who already have an existing distribution presence. 

Working with partners helps them to save infrastructure costs and helps them to make insurance available for even the most remote geographical locations.

[Related: Four New Consumer-centric Business Models in Insurance]

2. Digitizing Process Assistance

Most of the incumbents still rely on legacy systems and processes for underwriting, policy distribution, claims, and agent onboarding. The Insurance-as-a-Service model also assists companies to digitize and channelize insurance operations in a single system and then connect them to their engine. Mantra Labs is a leading provider of InsurTech services and offers plug and play products for digital insurers such as:

Insurance Chatbot: An NLP-powered that works on a self-learning model and is updated from time to time based on the interactions between agents and customers. It brings unparalleled benefits in terms of ROI saving licensing and agent salaries costs.

Paper to digital document parser: Mantra Labs’ Intelligent Character Recognizer allows users to convert and store paper-based or handwritten documents into a digital format. 

Today we need situation-dependent personal risk management products. Insurers can remodel their offerings based on real-time scenarios which will not only urge the customer to invest in the insurance policies but also work towards improving their customers’ health and welfare. For instance, you may not have comprehensive auto insurance. But, how good it will be if your insurer provided theft insurance whenever you enter a theft-prone area? It is a win-win situation for both — the policyholder as well as provider.

3. Digitizing Core Services

Some startups offer their services in a specific field of insurance. For instance, Mantra Labs focuses on customer engagement, new revenue streams, and security features. Some companies like Riskpossible help with underwriting, RightIndem for claims, and others for customer data management and fraud detection. 

Because these companies focus on specific insurance domains they are much more efficient in making Insurance services a winner.

[Related: Visual AI Platform for Insurer Workflows]


Mantra Labs is an InsurTech100 firm specializing in AI-first products and solutions for the new-age digital Insurers. For your specific requirements, please feel free to drop a line at hello@mantralabsglobal.com.


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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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