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Developments in AI give us new hopes. A recent study shows that 78% of banking executives believe AI would have a significant impact in the next few years. Let’s explore how much of a blessing AI is in QE.

What Do We Mean by AI in Testing?

Since, speed to market and quality assurance stand right beside each other in priority, banks are now looking to add extreme automation for measuring, analyzing, and improving their quality of offerings. This is where artificial intelligence has a significant role to play.



How AI Enhances Quality Engineering Across the Software Development Lifecycle in a Bank?


AI programs can help QE professionals to visualize the entire picture and find gaps in the quality that need immediate attention. This way, QA functions can be prioritized towards needs, that require urgent remediation.


Cognitive Algorithms and Their Role in QE for Banks





In order to successfully transform customer experiences, banking businesses need to accelerate time to market for both new products and new releases for existing products. The age of speed demands, companies to stand out through continuous development and delivery with assured quality, beyond traditional QA methodologies.

In a nutshell, AI can boost accuracy, maximize test coverage, and ensure faster turnaround for rapid digital transformation.


We help organizations implement early-stage testing with a strong focus on product quality which aids in producing defect-free code. Additionally, we also support non-functional testing in the early stages of SDLC and introduce extreme automation through service virtualization.

Not having to wait for design components to get in shape before testing has a huge impact on the robustness of your product. Learn more about Maveric and how it can be a trusted partner for your bank.

This blog has been published in DATAQUEST.

The Power of AI in Quality Engineering

Article by


Subramanian NN