Artificial intelligence is beginning to reshape how banks test some of the world’s most critical financial software, with new industry analysis arguing that quality engineering is becoming an increasingly important part of core banking transformation programmes.
Aspire Systems has published new guidance examining how banks are testing implementations of Temenos, one of the banking industry’s best-known core banking platforms.
Temenos is a Swiss banking software company that provides core banking, digital banking, payments, wealth management and AI-powered banking platforms.
The company claims its software is used by more than 950 banks worldwide, including many of the world’s largest retail, commercial, private and digital banks, such as Santander, ABN Amro, Standard Chartered, the Royal Bank of Canada, and Absa Group.
Testing the tech
Testing a Temenos implementation extends far beyond checking that individual banking functions work as expected.
Because the platform sits at the heart of a bank’s operations, handling everything from customer accounts and payments to lending, deposits and regulatory reporting, every software change has the potential to affect multiple interconnected systems.
That means banks must validate not only core functionality, but also end-to-end business processes, third-party integrations, APIs, performance under heavy transaction volumes, security controls and regulatory compliance.
According to Aspire Systems, financial institutions are increasingly using AI, generative AI and automation to support these testing programmes.
Rather than relying solely on manual regression testing, banks are adopting AI-generated test cases, synthetic test data, automated regression suites, API testing and continuous testing to cope with more frequent software releases and increasingly complex hybrid environments spanning legacy infrastructure and the cloud.
Aspire stressed these technologies “enable faster releases, improve compliance, and reduce risk” while helping banks modernise their testing strategies.
Traditional testing is over
In its analysis, Aspire argues that traditional testing approaches are no longer sufficient as banks accelerate software releases, modernise legacy platforms and introduce artificial intelligence into software development and operations.
The company wrote that “AI, GenAI, and automation enable faster releases, improve compliance, and reduce risk, helping banks modernize testing strategies and build resilient, future-ready banking operations.”
The emphasis reflects a broader shift across financial services. Rather than focusing solely on functional testing, banks are increasingly expected to validate performance, regulatory compliance, security, integrations and operational resilience across highly interconnected banking environments.
According to Aspire, testing programmes now need to cover core banking functions, payments, API integrations, regulatory compliance and performance and scalability, while supporting more frequent software releases.
The company also highlights the growing role of AI-generated test cases, automation and synthetic test data in helping institutions manage increasingly complex testing workloads.
Modernisation path
The publication comes as banks invest heavily in modernising core banking systems while simultaneously increasing their use of artificial intelligence.
Speaking at a recent company event, Switzerland-based Temenos CEO Takis Spiliopoulos explained the banking industry is rapidly moving towards an “AI-powered bank”, with AI readiness and intelligent core banking becoming central themes for future banking platforms.
The message is becoming increasingly clear. As banks compress release cycles and modernise mission-critical core systems, quality engineering is evolving from a final-stage validation exercise into a continuous discipline spanning development, integration, performance, compliance and operational resilience.
While Aspire’s publication is vendor-led thought leadership rather than an independent customer case study, it reflects a wider trend across financial services: AI is becoming as important to testing core banking platforms as it is to building them.
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