Quality is no longer a choice in the insurance industry – but is an essential requirement.
Quality assurance in insurance requires a revolutionary structure as innovation holds the top priority for the insurance industry. To succeed in the competitive environment, insurers need to achieve the highest quality standards with blazingly high speeds.
The need for robust quality assurance (QA) is becoming more essential as many insurance enterprises are progressing, getting more modernized, and securing their legacy environments in the digital era.
For an insurer, selling a policy is essential for the business but engaging the customer and upselling new products is a foresight that will bring business value. Back-end support employed with easy-to-use applications that are not just simple but responsive too, is very critical for the sector.
To achieve that, we need to employ an end-to-end ecosystem approach with intelligent and automated QA processes which in turn will help achieve quality and speed to promote faster business and technology change, as well as a better customer experience. This will also help the insurers to adopt the new technologies as per the requirements of their business objectives.
Now, let’s look at some of the key challenges of modern insurance, which QA can help overcome:
Effective blend and adoption of digital technologies:
With changing lifestyle choices, climatic changes, and overall technological inventions, the present-day risk scenario has also transformed. It demands IT excellence and organizations reimagining their business models and customer strategies. A robust digital transformation strategy requires a complete makeover of the traditional QA processes and infrastructure. QA transformation has made it so much possible.
Digitization of business is imperative to bring in more predictability and responsiveness for a seamless customer interface. Here, Data Analytics can be handy in ensuring a better customer experience.
Optimizing the user experience and gaining customers’ trust are two key benefits of digital transformation in the insurance industry. Also, it needs to be supported by a set of high-quality engineering practices that help mitigate the quality and velocity challenges that may arise.
Data Privacy and protection:
With the increased use of technology comes the increased need for data protection. Many businesses have started implementing and using data analytics and data-driven approaches for smart business solutions. It gives businesses great insights into client behavior. With these insights, new products or modifications to existing products can be developed with greater efficiency. There is no doubt that the security of customer data is critical, and businesses must ensure that their applications can cope with handling such a large amount of highly sensitive customer information.
To remain competitive, insurance companies need to be agile and adapt to business, user, and technological changes. Since development and testing trends are evolving, QA testing programs also need to evolve and should include practices such as core system testing. The testing of insurance applications requires testers who have a thorough understanding and core knowledge of the domain.
The line separating developers and test engineers will blur even more. Technical (i.e., programming), Agile, DevOps, and Automation skills will become a requirement for QA practitioners.
Nowadays QA is focused on determining whether an application can perform its intended function but soon QA resources will be viewed as an extension for the end-user. One of the responsibilities of QA would be to ensure a delightful end-user experience. QA must test that the application is easy to use, fast, produces rewarding results, supports the desired business outcome, and is just overall very good.
Quality assurance is made easier and more effective through automation within the insurance sector. Automation is the way to eliminate many manual steps in all insurance workflows and enhancing the quality of those processes. Its reduced need for manual data entry leads to a reduced scope of human errors. It has accelerated every step of the process from onboarding to billing to claims. As insurers, we must continuously innovate, implement best practices, and update ourselves to pass on that value to our clients and end-users.
A more connected world:
Insurers are looking for a solution that comes with a host of integration capabilities built-in. It provides the ability to control the interconnections, interfaces, relationships, and dependencies between enterprise, business, process, information, and IT capabilities, as well as system and service offerings. Microservices architecture and the use of APIs and web services continue to be the approach of choice for these integrations, and as we see more of these come to life, we would need to develop the ability to automate for these integrations.
As the integrations move from one environment to another, it is important to test the APIs and web services with data that will pass through the integration, credentials, access, and database connections, as well as the configuration settings that will change (such as endpoints) over time.
Core Platform and Domain expertise:
Each area in the insurance domain is crucial for the business and needs expert attention to ensure the end-to-end smooth transformation. To ensure high quality, Insurers need to have expert IT resources with domain experience who can work across channels and value chains to ensure high-Quality Assurance from Core Systems (Policy, Claims, Billing, Rating, and Forms) to Downstream Reports, Data Migration, and Application Testing. It would be a value add in the overall scheme of things.
Expectations that QA Resources is an extension of the end-user become the norm. QA is now more focused on creating a platform that involves adding value to the business. A robust quality assurance (QA) ecosystem is very essential for businesses to keep pace with the market and achieve quality with faster business and technology change, as well as a better customer experience