Who knew that digital banking which was once considered almost an impossible innovation would become a differentiator between ordinary financial firms and an extraordinary one? Yes, digitalization in banking has saved its spot by impressing customers with outstanding offerings and seamless experiences. No more standing in long queues in banks or waiting days, weeks, or even months to get a loan. Everything is now embedded in that 5-inch intelligent device and the job gets done in minutes.
Testing in BFS
One thing most banks ignore or rather miss out on is testing the quality of their services. Considering the complex technical architecture of a core banking system and the pressure to exceed customer expectations, automating the testing process is the ideal way to go as manual testing process is strenuous and time-consuming, hence, fails to satisfy customer needs. Also, most tasks are repetitive and even a small feature needs effective testing, which becomes mundane and burdensome in manual testing.
Adding to this, the increased number of features and offerings like omni-channel banking, cloud migration, etc., makes the process even more complex. Hence, the current trend is moving from Quality Assurance to Quality Engineering, which is a holistic approach in banking to maintain the quality of the services as well as decrease the time-to-market. Therefore, there is a demand for a smart assistant which can handle the complex testing process and yield compelling results. And that super smart assistant is AI-based testing.
AI-based Testing: The best thing since sliced bread
AI-based testing is an agile testing approach that executes end-to-end testing of all the applications including functional and non-functional requirements by leveraging advanced machine learning techniques. It eventually helps to reduce the TCO and increase the ROI of an enterprise in the long term.
Why AI-based testing for Banks?
The technical model of the banking software is mainly designed to ensure that the customer data stays private and the transactions are strongly encrypted. Banks integrate with 3rd party vendors for building an effective core with multiple services without compromising on the security and all these add to the complexity of the architecture. Upon this, customers expect the software to be up and running 24/7 and there is a minimal chance left for any maintenance mishaps. And the father of all the challenges is the volatile regulatory guidelines that the banks are expected to adhere to at any given point of time.
Therefore, it’s only obvious that there should be a promising testing tool which can ensure the quality of the software and its operational capabilities, comply with the regulatory norms, and ensure faster time-to-market. That is the reason why AI-based testing is becoming a favourite among bankers.
Benefits of AI-based testing
The core banking system of most banks is now becoming more agile as it uses the DevOps approach where both testers and developers work hand-in-hand to reduce time-to-market. Also, with most banks migrating to cloud, test automation is now more than necessary to test the effectiveness of the applications. With a proper AI-led framework, these are some of the benefits of test automation:
- Faster time-to-market
Using the shift-left approach, test automation increases the overall testing speed by providing self-healing scripts that identify any changes made in the application, auto-updates the defects in the defect tracking tool, analyses the severity of the defects, supports end-to-end testing, etc.This is the right testing approach that suits the DevOps culture and hence, the products are launched faster to the market.
- Enhanced customer experience
AI-based testing takes a comprehensive approach and tests each individual component of the software and identifies all possible defects right from the initial stages. This can include functional or non-functional elements of the application which directly or indirectly impact the overall customer experience.
- Open chance for innovation
Test automation performs different kinds of testing like unit testing, regression testing, smoke testing, etc., covering the entire application’s quality. Also, the automation scripts can be reused multiple times which reduces overall automation efforts by 40%. This gives ample time for testers to concentrate on exploratory testing giving a chance for new ideas and implementations.
With so many offerings, AI-based testing has proven to be the sure shot testing method preferred by several banks and tech giants. Hence,we, at Aspire Systems, are happy to introduce our go-to AI-based testing approach- Hyper-testing. Leverage the expertise of Aspire’s Quality Engineers with Hyper-testing.This unified approach is powered by AI-led test automation allowing enterprises to conduct tests at top speed and provide superior error-free solutions. With features like providing useful insights on powerful dashboard, live streaming of test results, integration for web, mobile, and parallel cross-browser testing, etc., Hyper-testing helps improve the overall performance capabilities of the application.
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