As banks and financial institutions race to embrace AI-driven development, cloud migration and continuous delivery, software testing is rapidly shifting from a technical function to a strategic discipline focused on resilience, governance and risk management.
Against that backdrop, professional services giant KPMG India and quality engineering multinational Tricentis have struck a strategic alliance aimed at helping banks, finance firms and large enterprises modernise quality engineering practices and scale testing across their increasingly complex digital environments.
The partnership combines KPMG in India’s quality engineering and transformation consulting capabilities with Tricentis’ agentic quality engineering platform, reflecting a wider industry shift towards AI-enabled testing, continuous quality assurance and risk-based software delivery.
Under the agreement, KPMG India plans to integrate the Tricentis Agentic Quality Engineering Platform into selected transformation programmes to help clients assess and improve release efficiency, software quality and risk management practices.
The two firms said they will support organisations as they move away from traditional testing models and adopt “more intelligent, risk-based, and continuous testing models aligned with modern DevOps and CI/CD environments.”
QA evolution
The timing of the alliance is notable, because across financial services, testing leaders are increasingly warning that the pressure to deliver software faster is creating dangerous gaps in quality assurance and operational resilience.
Insiders agree the software testing market is undergoing a significant evolution. It is rapidly transforming from a traditional quality assurance function to a more strategic enabler of business outcomes.
Moreover, financial institutions are rapidly shifting from manual testing to automation and continuous testing approaches to enable faster and more reliable software delivery.
That trend is one of the central drivers behind the KPMG-Tricentis alliance.
As enterprises adopt cloud architectures, AI-powered development tools and agile delivery models, quality engineering is increasingly being embedded directly into transformation programmes rather than operating as a standalone testing function.
Prerit Binjrajka, Partner, Digital Engineering and Quality at KPMG in India, said the partnership would combine “intelligent automation with performance testing, AI-driven end-to-end test management and continuous quality optimization.”
“We are combining intelligent automation with performance testing, AI-driven end-to-end test management and continuous quality optimization,” he stressed.
“KPMG in India’s alliance with Tricentis reflects our focus on combining domain knowledge, engineering experience and contemporary testing platforms to support clients as they evaluate and evolve their quality engineering approaches.”
Binjrajka added that “by bringing together our quality engineering capabilities and Tricentis’ agentic quality engineering platform, we aim to help organizations address quality considerations across modern delivery environments in a structured and scalable manner.”
The alliance also arrives as AI-generated code becomes a growing concern for software quality leaders.
Damien Wong, Tricentis’ senior vice-president for Asia-Pacific, argued that AI is fundamentally changing how software is created and therefore how it must be tested.
“AI is now permeating enterprise environments by actively writing code to solve complex business problems from simple prompts, redefining what was once the exclusive domain of human developers,” Wong said.
“Organisations want to take advantage of this, but they have to do so with confidence that the code is safe.”
For banks and insurers, this challenge is becoming increasingly urgent.
Both Wong and Tricentis UK and Ireland chief Andrew Power warned that many financial institutions continue to prioritise delivery speed over testing rigour.
Power said that “two thirds of UK financial services firms admit to deploying code changes without comprehensive testing, and two thirds expect software outages or business-impacting incidents to continue over the next twelve months due to poor software quality.”
“That’s not a lack of awareness; it’s a structural gap between speed and safety,” he said.
Wong has been even more direct.
“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,” he warned. “Speed is being pushed very hard.”
The implications are particularly significant in banking, where regulators increasingly expect firms to demonstrate resilience rather than simply prove that testing has occurred.
Power has argued that quality assurance is becoming a board-level concern as software failures create growing financial and operational risks.
“QA is rapidly becoming a board-level concern because the financial and operational impact of poor software quality is impossible to ignore.”
– Andrew Power
Power added that firms are increasingly being asked to provide “evidence of resilience, not just release readiness.”
That emphasis on resilience is reflected in the structure of the KPMG-Tricentis alliance.
The companies said they plan to support enterprises in adopting AI-enabled quality engineering, continuous testing and intelligent automation, while helping organisations move away from siloed testing functions toward integrated quality models embedded within DevOps and CI/CD pipelines.
The alliance will also focus on automation and analytics-driven testing approaches designed to improve efficiency, reduce maintenance effort and streamline release cycles.
For Tricentis, the agreement represents another step in its broader push to position quality engineering as a central control mechanism for managing software risk in regulated industries.
The company has increasingly championed agentic AI as a way to help organisations cope with growing application complexity and accelerating development cycles.
Wong previously described a future where testing teams can instruct AI-powered testing agents using natural language.
“Imagine you have a virtual performance engineer now, and you can use natural language to instruct it,” he said.
“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’.”
Yet both KPMG and Tricentis frame the opportunity as extending beyond automation alone.
The broader goal is to help organisations establish continuous, scalable and business-aligned quality engineering capabilities that can keep pace with modern software delivery.
That aligns closely with Elfield’s view that testing is no longer simply about finding defects.
“Testing is no longer an activity that takes place at the end of the development cycle but is integrated throughout,” he said.
As banks continue to modernise core platforms, introduce AI-driven capabilities and navigate increasingly demanding operational resilience requirements, alliances such as this suggest the future of quality engineering may be defined less by testing tools alone and more by the ability to combine transformation consulting, automation, risk intelligence and continuous assurance into a single operating model.
For financial institutions struggling to balance innovation with control, that may prove to be the real significance of the deal.
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