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10 Most Impactful AI-based Insurance Innovations of 2019

5 minutes, 5 seconds read

The year 2019 has been a benchmark in insurance innovations that brought in new value propositions to the industry. What’s more remarkable is — both traditional Insurers and Insurtechs are striving to offer simple, convenient, and value-added customer-centric products coupled with technology initiatives. Here are 10 noteworthy insurance innovations that shaped the industry this year.

  1. Augmented Intelligence
  2. AI-based Smart Automation
  3. Digital Insurance Broker
  4. Services Beyond Insurance
  5. Blockchain in Reinsurance
  6. Unconventional Partnerships
  7. Understanding Customers and Delivering Tailored Products
  8. Insurance on Demand Services
  9. Risk Intelligence
  10. Customer Education

10 Most Impactful Insurance Innovations of 2019

According to a recent EFMA-Accenture report, the insurance industry has witnessed growth in digital sales & services, Artificial Intelligence trends — especially machine learning and natural language processing (nlp), big data and analytics, cloud, intelligent automation, and blockchain.

However, insurance players are not just adding convenience through technology but also understanding the ‘actual’ customer needs and developing the products accordingly. Let’s discuss the impactful insurance innovations with their use cases in detail.

#1 Augmented Intelligence

While most insurers are leveraging AI to understand customers and their requirements; another idea that hits the list is to complement the knowledge of insurance employees during sales pitches and customer services. 

For example, Zelros is Augmenting intelligence of sales and customer representatives through real-time best product recommendations, advisory, and pricing based on studying the customer profile.

Zelros - augmented intelligence - insurance innovations

Similarly, Nippon Life Insurance Company has introduced an AI-powered TASKALL tablet for its sales representatives. This tablet identifies suitable prospects from the set of entire salesforce activities, thus enhancing the sales and customer representatives’ services. 

#2 AI-based Smart Automation

Smart automation corresponds to deploying intelligent technologies to gain massive operational efficiency and at the same time create value for the end customer. 

For example, South Korean Kyobo Life Insurance Co. Ltd. has developed an AI system BARO (Best Analysis & Rapid Outcome) to automate underwriting. The system uses NLP to allow sales and customer interactions in natural language.

In the same way, Religare incorporated AI-based chatbot in their workflow. Through this bot, the company has automated a number of operations like customer query resolution, customer engagement, and lead and ticket management.

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#3 The Digital Insurance Broker

In 2018, in the US alone, nearly 1.2 million people worked for insurance agencies, brokers, and insurance-related enterprises. This indicates the prominence of the brokerage in insurance. Brokers might not be directly involved in product development, risk evaluation, etc.; but they play a pivotal role in insurance distribution. 

For example, Gramcover, an Indian composite insurance broking firm is leveraging mobile technologies to minimize the inefficiencies and transaction costs in distributing micro-policies.

Also read – The case for a digital brokerage

#4 Beyond Insurance

The year 2019 also witnessed the entry of technology giants like Alibaba entering the insurance space, and people welcoming them made the competition even more fierce. The World Insurtech Report 2019 states that nearly 30% of customers are interested in buying at least one insurance product from BigTech firms like Google, Apple, Facebook, Amazon, and Alibaba. 

Insurers have thus realized to embrace the ecosystem-based digital economy to deliver richer customer experiences. AG Insurance’s Phil at Home is an example of ‘beyond’ insurance services to support customers in their day to day life. The app provides house maintenance services like plumbing, electricity, etc. along with medication reminders, food delivery, etc. to its elderly customers.

Also read – The Belgian Insurance Landscape

#5 Blockchain in Reinsurance

Blockchain or distributed ledger technology (DLT) brings transparency to a range of insurance processes along with the secure sharing of information. The innovative use of blockchain in insurance is to reduce redundant efforts. 

For example, the US-based Aon Benfield along with partners have developed a blockchain-powered reinsurance placement solution to bring brokers and reinsurers on a collaborative platform.

Similarly, the Hong Kong Federation of Insurers in collaboration with CryptoBLK developed MIDAS (Motor Insurance DLT-based Authentication System) to authenticate motor insurance policy documents across the network in real-time.

#6 Unconventional Partnerships

Insurers’ partnerships with Insurtechs, Fintechs, and external players are presenting an opportunity to explore new customer base, test different business models, and get access to new technology frontiers. 

For example, AXA partnered with ContGuard, which provides real-time cargo tracking services. Their product — Connected Cargo Solution gives customers 24/7 monitoring and data to AXA’s risk engineers to develop loss prevention plans. This also helps underwriters to quote the price with increased accuracy.

#7 Understanding Customers and Delivering Tailored Products

Addressing the customers’ demand for personalized services, Insurers have started applying AI to understand their sentiments and requirements. They have realized that real-time digital services unlock values for both carriers and customers.

For example, the UK-based Bought By Many helps people find insurance for uncommon assets like pets, shoes, gadgets, etc. The company also negotiates with insurers for the best deals.

#8 On-demand Insurance models

The World Insurtech report 2019 reveals that nearly 41% of customers are ready to consider usage-based insurance and 37% want to explore on-demand insurance coverage. While usage-based insurance models provide as-you-go premium coverage based on customer’s potential for risky behavior; on-demand insurance allows customers to get cost-effective and convenient coverage depending on their needs.

For example, The Dinghy is an app-based on-demand freelancer insurer. It is also the world’s first on-demand professional indemnity insurance covering public liability, business equipment, legal expenses, and cyber liability.

#9 Risk Intelligence

Insurers are deploying machine learning models for risk assessment and mitigation. It not only makes the underwriting more accurate but also boosts profits by diminishing risks.

For example, ZestFinance uses automated machine learning tools to correlate current and traditional data. It helps to effectively gauge risks and outreach potential new customers.

#10 Customer Education

Pricing still presents a bigger competitive advantage than many other insurance features. Accenture’s 2019 Global Financial Services Consumer Study states – more than 75% of customers can share their personal information for better prices. 

Therefore, educating customers about potential risks isn’t sufficient. Coupling this information with available products’ prices and benefits is a must. For example, Jerry, a California-based personal insurance marketplace checks if the user is paying the best price for the insurance services. Based on an initial questionnaire, their AI-powered tools takes roughly 45 seconds to compare quotes from leading insurers and suggest optimum rate to the user.

Also read “Top 5 smartest AI-powered machines on earth.”

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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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