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How does AI enhance software testing for your banking app?

Keywords: Software testing services, quality assurance services  

The BFSI sector is currently undergoing tremendous digital transformation. Just in the past three years, the demand for mobile banking services has soared. Banks are now adding newer never-heard-of services, introducing digital currencies, closing physical locations and going towards more inclusive and secure systems.   

A lot is happening in the digital banking landscape, which again raises the importance of banking software. Are software testing services for banks substantial and robust enough to meet the reliability constraints put forth by the digital customer? Are banks ready to serve clients entirely through digital mediums? Are transactions on these digital banking apps absolutely secure and easy to go through?  

The answer to all these questions lies in AI-POWERED SOFTWARE TESTING.   

Software testing, especially when backed by AI (artificial intelligence), can optimize the testing processes for complex banking and financial applications. AI-powered software QA (Quality Assurance) can help in automating the entire testing process and increasing test coverage by 100%  

Let’s explore this in better detail:  

The various ways AI enhances software testing in banking applications  

There is no question about releasing software into the market untested. Even the simplest applications need exhaustive testing that explores their usability, functionality, performance and security aspects.   

When it comes to banking applications, especially those with AI-powered features such as advanced UI (User Interface), chatbots, fraud detection features, etc., they need to be tested multiple times for performance and safety before being released onto the market.   

In the past, we’ve seen many infamous glitches in banking apps that have led to disastrous consequences. For example, a recent scam from April 2022 was uncovered in South Korea, involving a banking trojan named Fakecalls that infiltrated the core banking application of a famous Korean bank. Thousands of victims’ contacts, microphones, cameras and locations were left out in the sun, leading to various calls with phishing attempts.  

With user loyalty at stake, banks cannot afford such costly mistakes. 

Here’s how bringing AI software testing services into use can help banks in several aspects:  

Achieving higher quality through AI-powered QA optimization:   

AI-led quality engineering solutions help in future-proofing a digital bank’s environment. These solutions address the core methodologies and emerging technologies regarding open banking platforms, fintech integrations, AI-enabled analytics and virtual assistants.  

Accelerating development and the concept of crash  

AI-led solutions accelerate failure of banking software. Wait! Now isn’t that a sad thing? Well, not really. These solutions shorten the entire cycle of build- test-release time so that banks can achieve faster implementation of products and ideas. It helps them reach targeted business revenue goals way ahead of their competitors, thus implementing continuous quality.  

Producing Fast, error-free results through automation   

Because there is no manual intervention, AI-powered software testing is more reliable and quicker. Here the tests rely only on robust algorithms, computing power and quality data. In AI-based automated testing, the system executes the tests automatically, thus allowing software to diagnose and heal itself. ML (Machine Learning) enables the systems to learn and improve quickly with none or negligible human input. 

Software testing with AI can also eliminate test irregularities and inconsistencies that may arise due to manual interference. 

Identifying repetitive patterns in data  

Banking software generates a massive volume of data, making testing a time-consuming and strenuous task. Testers need the best possible combinations of data to make testing successful. AI can help in this regard by combing through this voluminous data and intelligently identifying repetitive patterns.  

Reducing testing costs and efforts  

Typically, software testing requires a considerable amount of time, investment and human effort. The right people need to be hired; the right testing platforms need to be decided. When banks are looking for quick test results and to deploy them sooner, artificial intelligence can be a helpful resource.  

Testing banking applications means validating the system’s data, repeatedly, thus making AI an excellent prospect for automated regression testing. This, in turn, can cut down costs, reduce the effort and help release software faster.  

Creating innovative, distinct test environments  

AI can help create unique test environments as it can identify issues easily. The automation of repetitive tasks clears the testing fast enough to leave the rest of the operations for human reasoning and creativity. 

Producing better software for the end-user  

In the end, it is all about creating dependable software for the bank’s customers. Artificial Intelligence algorithms can test banking apps a lot better. AI ensures efficiency and AI-based insights can help model real user behavior to test accordingly. Thus, allowing the development and test teams to fail fast and get to the outcome quicker and create a well-rounded application.  

Enabling frequent releases at shorter intervals  

Deployments and updates are now happening faster than ever. Previously, banking software was either released annually, twice a year, or quarterly if there was a good tech team.  

Currently, given the rise in frequency of use of banking apps, the demand for fixing apps in real-time has also risen. As a result, developers are on their toes, releasing updates and fixes every day. Many banking application developers have now embraced Agile and DevOps methods to keep up with this fast pace of releases, thus ensuring uninterrupted service and a great customer experience. AI-powered automation is the only solace for such fast-paced testing.  


Modern technology is a great enabler of innovative banking systems. With AI, ML, blockchain, etc., enabling digital customers to have more meaningful and relevant experiences with lending, investments, or other banking functions, there is absolutely no dearth of applications for these futuristic technologies in the BFSI sector.  

What is important here is the presence and aid of the right software testing partner who rigorously verifies and validates these digital assets to make them ready for the digitally conscious consumer. People’s money is no laughing matter, which is why the dependability, reliability and credibility of banking software are always under question.  

An experienced Quality Assurance Service Provider such as Qualitest, with its vast knowledge and expertise of AI-powered quality engineering solutions, can help deliver business-resilient applications that would be useful for years to come.  

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