As banks and financial services firms across Asia-Pacific accelerate digital change, a growing number are taking dangerous shortcuts on software quality, according to Tricentis.
The testing specialist is now pushing agentic AI as a way to help regulated organisations reconcile pressure for speed with the rising cost of software failures, amid rapid regional growth and expanding investment in financial services.
Speaking in Singapore, Damien Wong, Tricentis’ senior vice-president for Asia-Pacific, warned that the pace of delivery is increasingly trumping quality controls.
He described this trend as “scary”, pointing to Tricentis research showing that many financial organisations admit to releasing code without testing it.
“The pressure to deliver fast is sometimes driving this behaviour to cut corners and roll out a piece of software before it is thoroughly tested,” said Wong. “Speed is being pushed very hard.”
For banks and insurers, the financial consequences of these decisions can be severe. Wong said organisations could face average losses of between $500,000 and $5m due to software defects and outages, reinforcing why operational resilience, software quality and testing discipline are moving higher up the executive and regulatory agenda.
Agentic AI moves testing beyond co-pilots
To address these risks, Tricentis has been investing heavily in agentic test automation, positioning autonomous AI agents as a step change in how testing is executed.
Unlike earlier AI-powered testing tools that act as assistants or co-pilots, agentic systems are designed to generate test assets, execute them and analyse outcomes with minimal human intervention.
“Imagine you have a virtual performance engineer now, and you can use natural language to instruct it,” said Wong.
“You can say, ‘Test the system with a maximum of 1,000 concurrent users, return the results, and make some recommendations to improve its performance’.”
Wong said the rise of agentic testing does not signal the end of human testers, but rather a shift in how their expertise is applied.
“The pressure to deliver fast is sometimes driving this behaviour to cut corners and roll out a piece of software before it is thoroughly tested.”
– Damien Wong
As software release cycles accelerate and application estates grow more complex, AI-enabled engineers are expected to deliver far greater impact.
“Imagine one AI-enabled test engineer who is highly competent,” said Wong. “They’re going to be able to do the job of 10 or 20 engineers to cope with the speed of code development that’s going through the roof.”
This focus aligns with Tricentis’ broader product strategy, including its push into autonomous ERP testing and its emphasis on embedding quality earlier and more continuously across the software delivery lifecycle.
The company has also been strengthening partnerships aimed at helping banks apply AI-driven testing at scale, particularly as they modernise core systems and introduce new digital products.
Asia-Pacific growth outpaces global expansion
Demand for these capabilities is reflected in Tricentis’ regional performance. Wong disclosed that the company’s Asia-Pacific business grew by 42% year-on-year in the 2024 financial year, significantly ahead of Tricentis’ global growth rate of 26%.
Growth has been driven by two major trends in the region: large-scale application modernisation and generative AI-led digital innovation.
As banks migrate away from legacy, “monolithic and brittle” systems towards cloud-native architectures, the complexity and risk associated with software changes increase sharply.
“You have hundreds, thousands, or even tens of thousands of applications running all over your organisation,” said Wong.
“You make one change in one system or application, and there are potential impacts to other systems and applications upstream or downstream.”
This complexity has turned testing into a visibility challenge as much as an execution one. Wong pointed to Tricentis’ acquisition of SeaLights, an AI-powered software quality intelligence platform, as a key part of its strategy to help organisations understand software risk in real time.
“For example, if you’ve changed an API [application programming interface] and checked in the code, what sorts of tests have you run?” he said.
“If no tests have been done, it intelligently tells you that this is a problem. You’ll never be caught flat-footed if something goes wrong.”
The emphasis on software quality intelligence has gained urgency following high-profile incidents such as the 2024 CrowdStrike outage, which was triggered by a faulty configuration update.
For banks operating under tightening operational resilience regimes, including the EU’s Digital Operational Resilience Act (DORA), the ability to demonstrate testing coverage, change impact analysis and control effectiveness is becoming a regulatory expectation rather than a technical best practice.
Testing non-deterministic AI systems
As financial institutions integrate generative AI into both customer-facing and internal systems, they are also grappling with how to test non-deterministic models that can produce different outputs from the same input. Wong said this fundamentally challenges traditional validation approaches.
“There is no right or wrong outcome, but there could be things that are completely unacceptable,” said Wong. “So, you want to make sure that you’re able to define the guardrails and ensure you stay within them.”
While the market for testing intelligent systems is still maturing, interest is growing rapidly. Wong said a recent Tricentis masterclass in Singapore focused on testing intelligent systems was oversubscribed, indicating heightened concern around AI risk, governance and compliance. For now, however, most customers continue to use AI primarily to test traditional, deterministic systems.
“If no tests have been done, it intelligently tells you that this is a problem.”
– Damien Wong
Deployment preferences remain another sensitive issue for banks and insurers across Asia-Pacific. Tricentis supports both cloud-based and on-premise environments.
While the company has established cloud regions in Australia and Japan, with plans to expand to Singapore, Wong said heavily regulated customers often prefer hybrid or on-premise deployments.
“In Asia-Pacific, the trends have been mixed,” he said. “There was a huge trend towards going full public cloud, but there has been a bit of pullback. Many of the heavily regulated customers we work with elect to deploy our software on-premise out of security concerns.”
For customers using Tricentis’ cloud platform, Wong stressed that access to source code remains tightly controlled.
“We can see the metadata associated with your software builds to determine what modules have been changed,” he said. “But we don’t exactly know the code in them, so that insulates people from the fear that their code might be taken or stolen from them.”
As Tricentis continues to expand across Asia-Pacific and other high-growth regions, including Latin America, the company is positioning agentic AI, automated testing and software quality intelligence as foundational capabilities for modern banking.
For QA and software testing teams in financial services, the message is increasingly clear: speed without visibility and control is no longer acceptable in an environment where software failure carries operational, financial and regulatory consequences.
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