How Adaptive Software Platforms Are Changing the Game for Insurers

Insurance companies are breaking free from outdated legacy systems and turning to insurance software solutions that are adaptive to stay competitive in today’s digital world. This shift is driven by the open architecture these solutions use, very different from proprietary software that is built on rigid frameworks.

These adaptive software platforms are not just about automating processes; they fundamentally transform how insurers interact with their data, customers, and the market. Digital engagement is at the forefront of this transformation. Dynamic interfaces are empowering vendors, agents, brokers, employers, and administrators with a premium user experience across all digital channels. This means that insurance processes can be streamlined and tailored to meet the specific needs of different stakeholders which reflects on the bottom line.

Why Insurers Are Turning to Adaptive Software Solutions

Consider a mid-sized insurance company, struggling with the inefficiencies of a legacy system. Claims processing was slow, new product launches were delayed, and customer satisfaction was dwindling. To overhaul its entire operation, they implemented automated workflows tailored to their specific needs. They integrated real-time data analytics to understand and anticipate customer behavior, and rapidly rolled out new insurance products that were precisely aligned with market demands. The result? They saw a marked increase in new policy subscriptions.

This is the power of adaptive software - As insurers grow, their software should be able to adapt without a complete overhaul. No one wants to go through another round of evaluating and implementing new software. It takes up just too much time and resources. 

Future-proofed: Modern Insurance Software is both Adaptive and Scalable

 We have said it before and we will say it again: insurance is a complex industry, and the software systems that support it cannot be anything but complex. The most effective insurance software platform is the one that responds swiftly to market changes, regulatory updates, and emerging risks. Numerous emerging technologies make this possible.

Event-Driven Architecture and Real-Time Data Processing

Legacy insurance systems often suffer from latency due to batch processing, which limits their ability to provide timely insights and responses. Adaptive insurance software leverages event-driven architectures (EDA) to process data in real time. The  effectiveness of this technology in modern insurance applications is supported by these frameworks:

• Event Brokers: Event brokers (also known as message brokers or event buses) are systems that manage the transmission of messages between producers (publishers) and consumers (subscribers). They ensure that messages are delivered reliably and efficiently

• Stream Processing Frameworks: These frameworks compute data as it arrives providing real-time insights. For instance, a P&C insurer might use such a framework to continuously analyze data from IoT sensors installed in homes and commercial buildings. What this brings to the table is the immediate detection of risks such as water leaks or fire hazards. For instance, Chubb has deployed IoT leak sensors in over 300 buildings. In one instance, these sensors detected a leak in a residence hall at Providence College, allowing maintenance personnel to shut off the water supply before extensive damage occurred. This proactive approach has saved millions of dollars in potential losses and demonstrates how technology can make "invisible risk actionable".​   

Microservices Architecture and Containerization

Legacy systems are often monolithic, making it difficult to scale and adapt individual components. On the other hand, modern adaptive insurance solutions use microservices architecture to break applications into modular, independent services.

• Microservices Frameworks: These frameworks allow each service to be developed, deployed, and scaled independently. For example, an insurance provider might use microservices to manage different aspects of its operations, such as claims processing and policy management. This modular approach allows them to quickly introduce new products and features tailored to regional needs without affecting the entire system. 

  Container Orchestration: Containers encapsulate microservices, allowing them to run in isolated environments. An example is an insurer using container orchestration to manage its policy administration system. This approach ensures high availability and scalability, as containers can be scaled up or down based on demand, and updates can be rolled out without downtime. 

Advanced Analytics and Machine Learning

Legacy systems often rely on static analysis, which limits their predictive capabilities. Modern adaptive systems integrate advanced analytics and machine learning to improve forecasting and decision-making.

Predictive analytics in insurance leverages sophisticated machine learning algorithms and advanced statistical models to analyze vast datasets from diverse sources such as historical claims, telematics, and external data sources. Insurers can uncover intricate patterns and correlations by integrating and processing this data through ETL systems (Extract, Transform, Load). This enables dynamic risk assessment, real-time pricing adjustments, and automated underwriting decisions. Additionally, predictive models enhance fraud detection through anomaly and behavioral analysis.

IA and Robotic Process Automation (RPA)

Manual and repetitive tasks in legacy systems often lead to inefficiencies. Robotic Process Automation (RPA) and Intelligent Automation in insurance addresses these challenges.  

RPA excels in automating high-volume, repetitive tasks such as data entry, policy renewals, and claims processing, leading to significant reductions in processing times and error rates. 

Intelligent Automation in insurance processes combines advanced AI and machine learning enabling the system to learn from data patterns and make informed decisions. This includes complex functions such as underwriting, risk assessment, and fraud detection. 

By combining RPA's efficiency in routine tasks with IA's capability for sophisticated analysis and decision-making, adaptive software platforms achieve higher operational agility and accuracy. This dual approach ensures that insurers can swiftly adapt to regulatory changes, market dynamics, and customer expectations, maintaining a competitive edge in the industry.

Open Architecture and API Management

Effective integration of modern technologies with existing systems as well as new third-party solutions is crucial for adaptive insurance solutions. API-first designs and middleware solutions facilitate this integration.

• API Management: APIs enable standardized communication between different services and applications. For instance, an insurer might use APIs to integrate its policy management system with external fraud detection services, ensuring a seamless data flow and real-time fraud prevention.

• Middleware Solutions: Middleware manages data exchange between disparate systems. An example is an insurer using middleware to integrate a new risk assessment tool with its existing policy administration system, allowing for enhanced risk analysis and improved policy management.

Not All Insurance Software Is Equal

When evaluating a new insurance software solution, it's crucial to scrutinize the system's core attributes. A system lacking solid architecture and data integrity will ultimately prove unsustainable and unreliable. As data volume and user base grow, the system may struggle to handle increased demands, resulting in slower performance and reduced efficiency.

Ask these questions of your tech partner to get it right:

•  How does your system scale with increasing data volume and user base? Can you provide examples or case studies demonstrating successful scalability implementations?

• How does your system handle large datasets and complex queries?

• How do you assess and plan for the future capacity needs of your client?

• Can changes be implemented easily and new products launched swiftly? 

• Are new functionalities dependent on complete solution releases?

Adaptability and speed to market are indispensable in today’s dynamic environment, but don’t forget to inspect the engine!

 Partnering with insurance technology innovators like SimpleSolve can ensure robust implementation and optimal performance for your insurance solutions. We believe time is money and we have a very high and verifiable success rate in taking our Customers into production in under a year. We walk the talk so contact us today for a demo!