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The Adoption of Chatbots across Insurance

The global chatbot market is expected to reach USD$ 1.25B by 2025, and generate roughly $8B savings globally by 2022 itself. With chatbots disrupting a wide variety of industries already, the technology is becoming more popular in a variety of business use cases – especially within the insurance sector.

Chatbots are becoming more advanced

Chatbots are a natural extension of the push for self-service capabilities. Yet in spite of its growing popularity, according to a recent white paper published by Cognizant Research, almost 60% of insurers surveyed worldwide are yet to implement a chatbot. According to Cognizant’s research (validated with our own internal findings), bot capability is derived from the maturity of the bot; either basic, moderate or advanced.

What makes chatbots effective

Based on this spectrum, ‘basic’ implies that a bot is mostly rules-based and can follow only simple instructions often deferring to a human, whereas those bots that are closest to a true human-like conversation, are classified as ‘advanced’ in terms of their capability. The maturity level of the bot is determined by their performance and their ability to Communicate, Comprehend and Collaborate with the user, providing utility across the value chain. These three C’s are key factors in distinguishing an effective bot from an unsatisfactory one.

Of insurers that have utilized chatbots in their operations, a majority 68% utilise only a basic form of the technology. While insurers have already benefited by saving costs and reducing customer servicing time using them, there is still significant opportunity for the uptake of more capable, reliable and intelligent bots to be deployed across the insurance value chain.

Europe has the highest volume of basic maturity chat bots among insurers at 60%. Asia along with MEA promises the most potential in terms of size and CAGR to adopt chat bot technologies over the next five years. North America is still the largest consumer of ‘advanced’ bots in insurance compared to all other regions.

Chatbots – leading CONSUMER AI APP for the next 5 years

Limitations to overcome

Insurers need to focus on these limitations faced by chatbots to realize their business imperative.

  • Need of human-centric interface: Most of the time, interactions with chatbot are still robotic, providing the end-user with a frustrating non-human centric experience.
  • Inability to contextualize conversations: Bots are programmed to follow a specific sequence or an algorithm, causing an inability to understand the nuances of human language – that results in an unfulfilling and an inauthentic experience.
  • Scalability issues: Developers need to anticipate and program the bot according to the exponential rise in the amount of traffic that the bot might handle.
  • Privacy and data protection: Data is both an asset and a liability. Since customers often give away personal data while conversing with a chatbot, insurers need to prioritise their privacy and data protection regulations for that region.

Opportunity Landscape for AI-enabled Chatbots

Chatbots can be leveraged for both simple and complex insurance processes in order to create definitive business value. Distinct successes have been noted in areas of:

AI Chatbot in Insurance Report

AI in Insurance will value at $36B by 2026. Chatbots will occupy 40% of overall deployment, predominantly within customer service roles.
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Insurtechs will lead the pack

Among other reasons for the large-scale implementation of chatbots, is that insurtechs predominantly target the tech-savvy millennial and Gen Z population who are more open to change and disruptive innovation. Positive customer experiences are directly proportional to twice the referrals, thereby expanding business scope by breaking traditional customer-interaction limitations.

Reimagining Insurance with Chatbots

The insurance industry has reached a revolutionary crossroad that mandates insurers become digitally agile. Over the next few years, chatbots are set to bring about a massive change to the industry and Insurtechs are leading the way in bringing AI-powered chatbots to the insured customer.

  • Lemonade: The NY-based insurtech relies on its app-based chatbots, backed by AI, that can craft personalized insurance policies & quotes for customers, and respond swiftly to a variety of customer queries and process claims.
  • Next Insurance: The insurance provider launched a chatbot via Facebook Messenger through which small businesses can obtain quotes and buy insurance.
  • Trōv: The company has integrated a chatbot into its mobile app that handles customer queries and claims by seamlessly gathering incident related information from the customer.
  • LeO: The insurer recently launched a chatbot which helps schedule calls and meetings, collect leads and answer customer questions automatically – allowing agents to focus on other tasks.
  • Religare: It’s one of the top health insurers in India and a part of major financial service conglomerate. The company has integrated an AI empowered insurance chatbot, that focuses on learning from actual human interactions over a question-answer driven format to build a more intuitive chat based sales funnel.

There is a direct relation between the positive Customer Experience provided by the chatbots and the hike in the revenues. Almost one-third of the insurance business is expected to be generated via digital channels in the next 5 years. The companies that leverage AI-driven customer data for chatbots shall flourish far into the future.

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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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