While many financial services firms and other businesses are rushing to embrace automation to improve and speed up software testing processes, the industry should take a cautious approach, according to an industry insider.
AI-powered QA automation tools can certainly boost testing output and performances, but they are not, yet, equipped to respond to unexpected real-world scenarios, argues Victor Ionascu, who is the research & development director at French IT infrastructure firm Axway, headquartered in Paris.
Ionascu, who is based in Bucharest, Romania, sees that QA professionals are increasingly turning to AI to address the growing complexities of software testing.
And for good reason. “AI-driven automation can improve test coverage, reduce test cycle times, and enhance the accuracy of results, leading to faster software releases with higher quality,” he said.
However, automation testing, while valuable, often struggles with the time needed to develop robust tests and the limited ability to adapt to real-world, dynamic scenarios, Ionascu pointed out.
“The challenge of automated testing is not just about setting up automation frameworks or creating scripts, but also about maintaining and evolving them as the system grows.”
In fact, “when real-world scenarios emerged, such as unexpected network delays or different file formats, the automation failed,” Ionascu continued.
“The tests weren’t able to adapt to these dynamic changes, requiring us to manually intervene, rewrite, or adjust the scripts frequently,” he added.
“Even small system changes, like the introduction of a new encryption algorithm or an unexpected spike in data volume, broke the automated tests. This demonstrated the limitations of current automation tools in adapting to more complex, evolving environments,” Ionascu shared.
“Despite its value, test automation is not a silver bullet for dynamic and complex systems.”
– Victor Ionascu
He disclosed that in one of his projects, Ionascu and his team had to test an application that handled secure file transfers between multiple entities, including several banks and government institutions.
“The flow involved multi-layer encryption and we needed to validate the entire encryption and decryption process,” he said.
“Initially, the automation test case we developed worked fine for standard scenarios. We scripted the flow to encrypt files using specific algorithms, transfer them to a central system and verify decryption on the receiving end,” Ionascu explained in a recent InfoQ analysis.
However, in real-world scenarios the automation did not deliver.
The time required to develop robust tests that can handle real-world dynamic scenarios poses a major challenge, he noted.
“Many automated tests are brittle, they work well in stable environments but break when faced with unexpected changes or edge cases,” he added.
Therefore, automated tests still require constant manual oversight and significant maintenance, “especially when they involve variable conditions that are hard to predict during the initial development of test scripts,” Ionascu said.
“Despite its value, test automation is not a silver bullet for dynamic and complex systems,” he summarised.
Ionascu stressed that a key challenge currently is to ensure comprehensive test coverage.
“When dealing with complex systems, especially in sectors like banking or finance, where we handle secure, multi-step data transactions, it’s nearly impossible to cover all edge cases manually,” he explained.
“The risk of missing corners of impactful workflows increases with complexity. The struggle lies in ensuring coverage without compromising timelines,” Ionascu added.
AI is here to stay
Despite automation not being quite there yet, Ionascu is keen to stress the added value of artificial intelligence-powered testing mechanisms as he understands why many banks, financial services firms and other companies are rushing to embrace the relatively young technology.
The seasoned tester often uses artificial intelligence in both manual and automated testing.
“I use AI-driven test generation tools like Amazon CodeWhisperer and ChatGPT to assist in the creation of automated test cases, reducing the time it takes to write complex scripts,” he elaborated.
“These tools help me generate dynamic data, create edge case scenarios, and even suggest security vulnerabilities that I might have missed,” Ionascu continued.
So AI tools can enhance both manual and automated testing workflows, Ionascu stressed, as he concluded that they help automate repetitive tasks, such as test case generation and bug triaging, allowing QA teams to focus on higher-value activities like exploratory testing and quality strategy.
Axway growth plans
Ionascu, Axway, made headlines earlier this year as it struck one of the biggest software of 2024, when it acquired Sopra Banking Software, a global financial technology company that serves hundreds of banks and financial institutions around the world.
The merged entity created France’s largest publisher or enterprise software, resulting in one of the world’s largest players in the QA space. The combination has around 5,000 employees in around 25 countries.
SBS was previously owned by European digital consultancy Sopra Steria, also based in the French capital.
The merged combination is headed by former CFO Patrick Donovan, as chief executive officer, and Eric Bierry, the former chief of SBS, who has taken on the role of Deputy CEO.
Sopra Banking Software (SBS), also based in Paris, was a global financial technology company that serves banks and the financial services industry “to reimagine how to operate in an increasingly digital world,” as the company marketed itself.
It currently works with around 650 financial institutions and large-scale lenders in 80 countries worldwide. Clients include Standard Bank, Santander, Société Generale and Rabobank.
SBS’ cloud platform offers a composable architecture to digitise operations, ranging from banking, lending, compliance, to payments, and consumer and asset finance.
Last year, the company generated revenues of just under €340m. The combined entity is expected to have estimated revenues of around €650m, well beyond Axway’s medium-term ambition as the company will be more than doubling its current revenue.
The takeover meant a major push into the global testing space for Axway. In recent years, it signed up one financial services client after the next and managed to venture well outside its home market of France.
Most recently, SBS signed a major deal with BTK Bank in Tunisia to implement a major banktech upgrade.
The QA contract is a good example of the relatively small and medium-sized finserv-market SBS is eyeing and which is responsible for much of its annual growth, such as regional banks, trading houses, smaller central banks and other financial services firms and entities looking to improve or mature their digital resilience.
Looking ahead, Axway said that, in 2025, it will pursue an annual organic growth rate of between 2% and 4%, with a target revenue of around €700 million and a margin on operating activities of between 14%, around €100 million, and 16%.
By 2027, Axway ambitions to achieve revenue above €750m and a margin on operating activities of more than 17% and a year later, by 2028, the Group is aiming for a margin on operating activities at around 20% of revenue.
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