With record-high inflation, climate change, and an economic downturn on the horizon, the insurance industry is in a pressure cooker of unpredictable change. Sometimes this change happens over time. Sometimes it seems to happen all at once. To come out on top, insurance companies need new workflow and operations strategies that leverage process automation to streamline processes, reduce errors, and improve the customer experience.
Learn more about the similarities and differences between code coverage and test coverage, and how they help you create better software.
Artificial intelligence (AI) is now well and truly mainstream. Once the preserve of futurists and doom-mongers muttering about job losses, it has become a global watercooler topic thanks to the rise of ChatGPT, which promises to transform the way the entire world goes to work. But AI has been a vital tool in the developer’s armoury for a while. It has given us new ways to optimize workflow and focus on those high-level tasks that will be forever human.
The NodeSource-GitHub partnership is a game-changer for developers seeking to build secure applications directly integrating NCM’s (Node Certified Modules) powerful security features into their GitHub Actions workflow.
Choosing one over the other can come down to a few key differences. Let’s take a look at both to help you make an informed decision.
Leading insurers are prioritizing claims process automation. Why? Because expenses related to preparing, processing, paying, and adjusting claims represent the most significant share of an insurer's operating costs. Even more than that, 87% of policyholders say the claims experience directly impacts their decision to stay with an insurance provider. But for many insurers, complex workflows, siloed data, and disparate systems have turned the claims process into a painful customer experience.
Hello there!! I’m excited to share my learning experience with you in this exciting new blog post so that you may better comprehend the area of performance testing. I was curious about the performance testing team’s work and the nature of their job until a few years ago. In my previous organization, it was a distinct vertical with a completely different reporting structure from the Quality Assurance domain.
Testing asynchronous APIs (AsyncAPIs) is becoming increasingly important as more and more APIs adopt asynchronous communication patterns. ReadyAPI now supports testing of AsyncAPIs, making it an even better tool for API testing. In this blog post, we’ll provide step by step guidelines on how to import your AsyncAPIs from SwaggerHub into ReadyAPI and how to test them. Hopefully, this will help you get started with testing your own asynchronous APIs.
In a world where 2.5 quintillion bytes of data are created every day, it’s not surprising that organizations want to harness the power of being data-driven. In our 2022 Data Health Barometer, 99% of companies surveyed recognized that data is crucial for success — but 97% said they face challenges in using data effectively. Perhaps in response to those challenges, 65% of companies reported that they'd started a data literacy program.
