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Catch and keep more customers with a digital insurance platform

Insurance Platform Providers: Insurance Platform Technologies That Belong in Your Tech Portfolio

Before there were computer platforms, there were two other important platforms.

  • A constructed riser that you stand upon.
  • A position you are taking, often political in nature.

Today’s insurance platforms actually contain elements of both of those definitions. The system platform that you build is the technology structure upon which you will base your business operations. Your business will, figuratively, stand upon it.

Your platform decisions are also open to opinion, though we would offer up that some of these decisions are too crucial to warrant any argument. Your opinion, however, is important to how your organization will use the platform to conduct its business. The construction materials of the past were effective, but for today’s digitally oriented customer and insurer, they are far too constraining in terms of speed, flexibility and performance.

With this in mind, I would like to share our perspectives on what a timeless insurance platform looks like. Even though you may be familiar with each component we will discuss, the entire focus of the discussion is how these components work together to establish a foundation for growth and innovation. We’ll also point out how they are built to last, with flexibility to adapt and grow as the market and your customers shift and change. You’ll find all of these insights (and more), in Majesco’s upcoming thought-leadership report, Insurance Platforms: The Digital and No Code / Low Code Platform.

Using Platforms to Engage Customers

To set the stage, let’s think about how we acquire and engage customers through different channels. In most lines of insurance, we traditionally capture customers through agents and brokers. This could be likened to catching customers like you catch fish — with a rod and reel, one fish at a time through a great number of fishing agents, and many casts between catches. Some insurers have established direct models where we capture customers based on their demand – they come to us to evaluate and buy – we try to entice them with “unique bait” that provides a compelling and easy experience.  And then there are partnership models where we reach customers in bulk through affinity groups or group / voluntary products through employers. This is like using a net — more like professional fishing companies might use in the waters of Alaska or Maine.

But what if we designed our business model, processes, products, channels and tracking so that fish, regardless of channel, would voluntarily engage and swim into little company lagoons without us having to chase so much? We could design products and channels that provide a unique, personalized experience to fit the swimming life of a fish, going with the currents and trends and offering what they need when they need it, wherever they may be.  But we need the right technologies that will support this varied journey and enable us to easily change course when opportunities or market shifts occur. 

The heart of the insurance platform is an orchestration of next gen technologies including cloud-native computing, microservices, APIs, new data sources, model and meta-data driven, no code/low code capabilities, and artificial intelligence and machine learning, coupled with a vibrant ecosystem of partners that provide innovative or complementary products and services. It allows insurers to completely change the way they operate and fish. A unified combination of components enables insurers to shift from being the owners of complex core systems to become the owners of greater technical agility and flexibility, digital fluency, innovation and speed to value that fits today’s pace of change and fits today’s customer appetites.

Seven Key Platform Components

To manage changing customer demands, it is imperative that insurers utilize a digital platform that can provide the speed, agility and cost-effective mediums to digitize, optimize, and innovate – in other words, enhance the customer journey and accelerate new innovations, all while driving sustainable growth.  This requires different technologies.

Cloud Native Services

What is not possible with traditional legacy systems is now possible with cloud deployment as long as the platform is architected for the cloud and not retrofitted to run on external servers with architecture designed for expensive on-premises deployment and upgrades.

"Cloud Ready," which characterizes the latter scenario, is typically used to describe an application that can be deployed in a public or private cloud, while a "Cloud Native" application is purpose-built for the cloud using microservices architecture with DevOps and Continuous Delivery capabilities with lightweight infrastructure needs such as containers. The advantages of Cloud Native apps are numerous, and include:[i]

  • Updatability: Always up-to-date and available
  • Elasticity: Can scale as needed
  • Multitenancy: Can work in a virtualized space and share resources with other apps
  • Connected resources: Flexible network resource connections don’t break if changes occur
  • Down time: Redundancy in the cloud reduces impact of outages
  • Automation: App management is automated
  • Modular design: Allows functions to be shut off when not needed and updated individually
  • Statelessness: Apps are not tied to infrastructure

A cloud-native platform opens the door to new ways of doing business, engaging with customers, bringing products to market faster and capturing rapidly unfolding market opportunities.

Microservices

A microservice architecture philosophy is to design a single purpose service that can be independently deployable and would not impact the platform ecosystem of services as long as the interface of the microservice is not changed. In simpler terms, we can characterize a microservice as a “micro application” that enables a specific granular business function like payment, issue, policy documents, FNOL, etc., which is loosely coupled with other functions.  The “micro application” can be deployed independently and can also communicate through well-defined APIs with other “micro applications” that serve other business functions. This approach is in stark contrast to “Monolith Applications,” such as policy management systems, billing systems, and claims systems that work as an aggregation of multiple business functions tightly woven together and deployed as a large monolithic unit.

In contrast, a microservices architecture decomposes a large unit into fine-grained, single-purpose, self-contained and independently deployable business services that enable rapid changes, opening the possibility of multiple daily change deployments instead of waiting for the periodic release cycle. Using microservices across various apps, insurers can orchestrate a composite user interface that is a tailor-made customer journey that can be enhanced quickly based on customer feedback. 

Model and Metadata-Driven

Over the last decade many insurers have realized that they have outgrown their systems.  As insurers cope with high data velocity and stringent regulations using a metadata driven design approach, not only is the system easier to use but it also reduces the time needed to implement new data sources.

But what is metadata? To put it into the simplest of terms it’s data about data. Metadata plays a critical role in investments in data warehousing, data mining, BI, customer relationship management, enterprise application integration, and knowledge management.[ii] A metadata-driven development model for building core system applications is a way to “futureproof” enterprise applications and plays a big role in insurance transformation, especially as the industry is transitioning to a platform economy.

The key focus of a metadata-driven model is integration, reuse and automation. A metadata-driven model permits interoperability by enabling data to be exchanged among many disparate platforms, data structures and interfaces.[iii]  With a metadata-driven model, insurers get a solution that is agile, uniform, easy to scale and maintain.

APIs

In this digital age, vibrant platform ecosystems are the foundation for creating new value by combining different APIs. With the explosive growth of new data sources, InsurTech solutions, emerging technologies and more, the demand and need for integration is exponentially growing, creating further complexity and often added costs.

An API-first approach has dramatically changed these dynamics. An API is a set of programming instructions and standards for accessing web-based solutions. An API-first approach has enabled many software companies to directly publish their API, so their partners can embed it into their solution in order to design and provide a seamless customer experience. Amazon and Netflix APIs are a few of the best-known examples. They are used by other businesses to link to Amazon and Netflix services with updated products, prices and content, right from within their own websites or apps, making it easy for customers to buy.

API Gateway

As the number of APIs grows, the need to manage, control and secure them also becomes more important – and complex. An API gateway is the core component of an API management solution, which provides metering, workflow management and developer self-service. It sits between clients and apps and accepts and coordinates calls from clients to those apps, instead of clients sending requests to individual apps. An API gateway is an essential tool to secure, scale and accelerate API traffic between apps.

New Data Sources

Data is a strategic asset and a critical source of competitive advantage for identifying unserved or underserved markets, tapping into profitable niches, reducing or eliminating risk, driving channel optimization, enhancing service and improving customer experiences. Combining data from traditional internal and new external sources can improve the richness of information used to identify new business opportunities and make better operational decisions, which are increasing the gaps between insurance leaders and those falling behind.  

The insurance industry has numerous established providers that have supplied data for pricing, underwriting, fraud detection, marketing and other key business operations. The InsurTech movement increased the number and variety of data providers that offer both traditional and new types of data.  Many factors are driving interest in and use of data providers, including better data for underwriting, enhancing the customer experience, and the need for large datasets for training artificial intelligence and machine learning models.  The insurer must also have the ability to bring these diverse data sets together within a context for building insights to realize their competitive advantage. In the platform business model, the insurer is able to get all the specific data about a person or business that allows them to rapidly set up a product and assess the risk specific to the customer based on their unique situation, region and risk profile.

Artificial Intelligence and Machine Learning

Artificial Intelligence (AI) is the tool of choice for many insurers and InsurTechs for streamlining and simplifying complex insurance processes.  Its power to solve traditional insurance problems is being driven by advances in AI research, the explosion of new data sources and, importantly, the massive, scalable computing capacity in the cloud. This must be a significant area of focus for insurers.

Most insurers are very familiar with the creation of predictive models and predictive analytics. Actuaries or actuarial services have been active users of these types of advanced analytics for a long time. With new out-of-the-box AI providers like DataRobot and Gradient AI, even smaller insurers are now able to utilize the power of predictive models to improve operational decisions. Artificial intelligence and machine learning in the digital insurance platform are creating considerable opportunities for new sources of value for both insurers and their customers. Just a few of the emerging capabilities include:[iv]

  • Behavioral-based pricing and continuous underwriting: Streams of data from connected devices like fitness trackers and cars enable real-time, usage- and situation-based pricing and underwriting.
  • Enhanced customer experience: AI-driven chatbots offer streamlined, personalized interactions and algorithms drive faster underwriting decisions.
  • Personalized coverage: Customers can customize coverage for specific items, events and time periods.
  • Faster claims settlement: AI-driven claims processes settle claims faster while also improving fraud detection

Platform Transformation to Go

Are you ready to change the way you operate and fish?

While you may be using and integrating some of these technologies into your tech portfolio, you may be using multiple solutions rather than a single digital insurance platform that can enable your digital transformation journey and integrate with your core platforms. Without this cohesive approach, you could be missing the complete realm of opportunities that an integrated platform can provide. The need for holistic transformation is greater than ever. 

At Majesco, we encourage insurers to begin with technologies that are built to handle platform components, such as API-first systems, pre-integrated microservices, no code / low code, and data sources that are ready to be “plugged in” at a moment’s notice. Our Majesco Cloudinsurer® core  and Majesco Digital1st® Insurance platform offerings are built for speed in implementation, richness in functionality and they provide the agility to innovate and engage the customer. For more on the power of digital platforms, be sure to listen to a recent Majesco webinar, Digital Transformation Tipping Point: Digital Platforms Redefining a New Era of Leaders.


[i] Patrizio, Andy, “What is cloud-native? The modern way to develop software,” InfoWorld, June 14, 2018, https://www.infoworld.com/article/3281046/what-is-cloud-native-the-modern-way-to-develop-software.html

[ii] Rogers, Phillip G., “Building the Business Case for Metadata in the Enterprise: Looking At Models, Architectures, and Business Processes As Building Blocks for Cost Benefit Analysis and ROI,” School of Public Health, Instructional and Information Systems, UNC Chapel Hill, https://www.slideserve.com/albert/building-the-business-case-for-metadata-in-the-enterprise

[iii] “Metadata and Its Importance in a Data Driven World,” Villanova University, October 29, 2019, https://www.villanovau.com/resources/bi/metadata-importance-in-data-driven-world/

[iv] Zagorin, Edmund, “Artificial Intelligence in Insurance – Three Trends That Matter,” Emerj.com, June 10, 2019, https://emerj.com/ai-sector-overviews/artificial-intelligence-in-insurance-trends/

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