Importance of Artificial Intelligence in Banking Software Testing

The current 5 years ongoing trend speaks of 50 million deployments in 2015 annually, which if broken down would be one in every second. There is no reason not to believe that by the end of 2020 and beginning of 2021, the number of software deployment would certainly rise. Can you afford to release your software without being tested? No, you cannot.

Testing software before its release has become a conventional choice for software developers and testers. Building a feature-enriched application does not just end with development, it extends further beyond checking the features and functionality to ensure that your banking and financial application breathes life with flawless performance and integration. Right from testing the application acceptance by customers to identifying the defects and fixing them, testers monitor the entire software development lifecycle.

Testing allows you to protect your financial applications against potential failures and risks involved during its implementation. Software testing has a larger purview, as through APIs, one application interacts with another. As testing moves towards automation, it aims for higher accuracy and a leap towards digital transformation.

Improving Software Testing with AI

We are now progressing towards Software Testing powered by Artificial Intelligence with the growing need of achieving rapid and error-free results through automation testing. The entire foundation of AI-based software testing thrives on data, computing power and robust algorithms. In contrast to manual testing, AI-based automated testing enables the machines/system to execute the test codes automatically and respond better with minimal human intervention. AI empowers machines to learn and improve with very less human cognitive input. AI is a step ahead, which allows the software to test, diagnose, and heal itself.

Why AI is important in banking software testing?

  • Software testing requires developers to acquire possible combination of data, which could be a time-consuming and strenuous task. AI can smartly recognise the available data combination through automation based on repetitive patterns of data access.
  • Software testing requires more time, human resources, and investment. Artificial Intelligence can be a suitable option for developers who need to deploy the financial applications promptly, even with inadequate infrastructure.
  • Since testing is mostly checking the data repeatedly, which already exists in the banking software and has been running in close succession, AI can efficiently help in automating testing processes with minimal human effort, cost, and time.
  • The developed applications can recognise the issues and create unique and innovative test environments with the help of Artificial Intelligence. This leaves room for AI to automate the testing of repetitive tasks and leave operations to human creativity and reasoning ability.
  • The repetitive task not just requires extensive human effort and time but is also prone to errors and inconsistencies. AI-based automated testing will help in eliminating these testing irregularities.
  • Artificial Intelligence algorithms can be extremely helpful for testing banking software, ensuring its efficiency, and making it smarter for the end-user. AI algorithms imitate human actions and operate accordingly. Applying machine and deep learning algorithms can optimise the process with Artificial Intelligence.
  • Testers can detect bugs more efficiently in less time by using a smart algorithm making the application more reliable and accurate for users. Developers can use these outcomes to improve the product and learn through errors.

AI advantages in software testing

Artificial Intelligence-based testing provides solutions for problems that may surface during manual testing and are subject to frequent changes. AI testing saves time and money facilitating faster delivery to the market. With very less human intervention, software testing can be steadily conducted using artificial intelligence can be done steadily without much human intervention. Using artificial intelligence software automated testing tools yields high productivity. Testing software requires performing the same test steps repeatedly. AI-empowered testing tools enable you to execute these repeated testing more accurately and provide a detailed result and feedback every time the test is executed. AI-based testing improves the test scopes and software quality, enhancing the overall test coverage. As compared to human testers, AI bots can produce hundreds of test cases based on customer requirements.

Continuous Testing with AI

Previously, software was released annually, bi-annually, or quarterly; presently there are monthly or even more frequent releases. Developers and testers are now embracing Agile and DevOps method to accelerate the product launch process. To resolve errors and defects in software, which may arise because of quick market release, organisations are implementing continuous testing for uninterrupted performance to ensure user acceptance. It involves testing software early and often, ensuring that your customers enjoy an outstanding user experience. The gaps in testing applications at the complete phase of software development lifecycle, and later releasing it in the market can be bridged by continuous testing. But over time if these gaps widen then it will be necessary to take a step ahead.

With constantly reducing timeframes of software releases, continuous testing may not be enough to keep up the pace of faster delivery. We would need strong and intelligent additional support to be able to provide outstanding performance speeds and uninterrupted user experience. AI and Machine Learning are well-equipped to expedite the complicated phases of simultaneous software development and testing. Tasks that require human learning and reasoning abilities to automate will be made easier with AI techniques.

Concluding AI in Banking Software Testing

The rise of AI and full-stack frameworks can control increasing technical complexities and the rate of changes in software at its development phase. As the capabilities of AI are constantly evolving in software testing, we at Yethi, deliver accurate, extremely rapid, and high-efficiency testing capability with our 5th generation AI-driven codeless automation testing tool-Tenjin.

Its intuitive features can help you to reduce the regression testing load, repeated testing of the same set of tests, and launch your product within a strict timeframe. With a repository of 450K+ test cases, we can cover end-to-end testing of your applications, saving you time, money, and effort. With over 6 years in the industry, we have built our reputation by offering complete QA solutions and support to our 70+ BFSI clients across 17 countries.