By Dinesh, Chief Software Officer, Novac Technology solutions
A year can make a lot of difference. The pandemic has upended various industries, and the insurance industry has shifted the consumer needs, habits, and journey with virtualization, prompting the galore of structural changes across the industry. 2021 saw the increased demand for service-based models, innovative products, and ways to interact with customers on new channels.
The foundation of the insurance industry is based on offering products and services to the customers and protecting them against any unforeseen circumstances while handling the technology-driven shift in the industry as a whole. Insurers prefer buying insurance digitally and interacting with advisors on various platforms.
With millennials forming the majority of the customer base, it’s time for the insurance industry to adapt to the trends in 2022. Let’s take a look.
Cloud-Insurance-as-a-service
Insurance-as-a-service is a digital insurance service that includes simpler claims management, customer onboarding, and customer support. The service runs on a dynamic operating model, a flexible, data-driven, and modular plug-and-play product suited to fit any digital insurance ecosystem. There are three distinct approaches to the insurance-as-a-service model.
– Internal Process Digitization
– Core Service Digitization
– Full-stack Digitization
With all the transformation efforts, insurance is becoming readily available to consumers directly within the ecosystem, thereby opening up an avenue of smart products that are data-driven, relevant, and tailored to current needs.
Process Automation and Virtualization
Another holistic solution for digital transformation is intelligent automation that uses artificial intelligence, machine learning, and robotic process automation to build end-to-end business processes and workflows that can learn, think, and modify over time. Automation and virtualization have impacted the insurance industry in various facets such as policy checking, data entry, claims process, etc.
In the insurance industry, RPA refers to the use of rules-based, low-code software bots to handle repetitive tasks, such as customer information, extracting data in claims, performing background checks. Insurers can improve accuracy and efficiency by freeing up both human and hardware resources for more strategic tasks and decisions.
With process automation and virtualization, critical insurance operations such as,
– Faster insurance claims processing
– Higher Customer Satisfaction
– Increased Data Accuracy
– Rapid cost Savings
Microservices Architecture for Insurance
For starters, microservices architecture is a distributed system built up from multiple modules that can communicate through APIs or modules that can be scaled, updated, and deployed separately. The idea of smaller, composable pieces is working together in a monolithic industry such as insurance, where multi-channel distribution, quicker time to market, real-time data analytics, and faster response times are paramount.
Microservices architecture provides a layer of abstraction that decomposes large core insurance tasks into single fine-grained purpose, self-contained, and independently deployable APIs for faster decision time and enhanced customer journey mapping based on market needs. With Microservices architecture, insurance organizations can
– Scale to market quicker
– Build better insurance products
– Optimize speed and performance
Predictive Analytics
Predictive analytics in the insurance industry uses various tools such as data mining, predictive modeling, statistics, Machine Learning, and AI to make predictions on the risk, underwriting and policymaking, and probabilities on future events. Insurers see predictive analytics to improve the customer experience while eliminating fraud.
Predictive analytics improves the risk model accuracy by collecting relevant client information, including credit history, driving record, and more. It can apply predefined underwriting guidelines to accept or decline the application and move forwards to the following steps to make more accurate predictions about a client’s risk profile.
By doing so, underwriters gain ‘cognitive insight’ to identify elements relevant to risk evaluations with traits customized with AI-based ranking systems that aid them in calculating the optimal policy by connecting insight with action.
With predictive analytics, much of the overhead costs are removed by automating fraud detection via AI-based pattern recognition in any facet of the insurance industry.
Telematics
Telematics is an amalgamation of telecommunication and informatics, where the auto insurance industry uses the technology to track, store and transfer driving-related data. This data comes in handy while understanding driving behavior and charging the approximate vehicle insurance rates.
Insurers can begin calculating premiums with self-reported information from telematics and store the results for meaningful interpretation of the insurance’s underwriting business. The data includes the car owners’ risk profile based on the distance covered, average speed, frequency of use, and overall driving skills and charge a premium rate accordingly. With telematics, the car insurance facet can provide several usage-based insurance types such as,
– Pay as You Drive
– Pay How Your Drive
– Pay as You Go
– Distance-based Insurance
How your insurance organization can stay on top of the trends?
The above tech trends highlighted the need for the insurance industry to dramatically reshape from the foundations, creating significant opportunities for both the customers and the insurers to scale up significantly. From attracting customers to delivering the right insurance through various channels, insurers must build engaging and personalized journeys with a little bit of innovation and giant technological leaps in the coming times. The insurance business must stay ahead of the growing competition with a leading enterprise solution that can aid in taking a more significant step towards technological innovation.
Among all sector’s BFSI has been the top used RPA automation technology in their process and it is still increasing rapidly.