When EQ Bank launched in 2016 as the digital-only banking brand of Equitable Bank, it set out to “reimagine how customers interact with their financial services provider, offering a smarter and more flexible alternative to the complexity and hassle of traditional banking.”
Based in Toronto and operating across Canada, EQ Bank is powered by Equitable Bank and has grown rapidly: in less than a decade it has reached service of “half-a-million consumers” and has since expanded into business banking.
For QA software testing teams in banks and financial services firms, EQ Bank’s journey offers a compelling lens into how a challenger bank aligns core banking infrastructure, cloud deployment, digital product speed, automation and regulatory readiness.
Modernising the core
EQ Bank originally launched using a traditional on-premises deployment of the Temenos Core Banking solution to underpin real-time transaction processing and digital product development.
As volumes and pace of change increased, the bank evaluated how to scale infrastructure for “rocketing volumes of customer transactions.”
It concluded that “we realised that a cloud-first model would unlock benefits in terms of scalability, reliability, and security.” Plus, we knew the cloud would help with product development and give us more time to think about digital innovation rather than infrastructure management.”
In 2019, EQ Bank moved to a version of the Temenos solution running as a SaaS in the public cloud, hosted on Microsoft Azure. The rollout took approximately 12 months.
“The support from Temenos accelerated the changeover, and because we run the systems with minimal customisations it minimised any complexity. Our learning curve on the Temenos SaaS was quick and easy,” the bank wrote in a summary.
For QA teams, this transition is a vivid example of how moving to a cloud-native core influences testing strategies: fewer heavy customisations, more reliance on standardised integration, performance scaling checks under elastic load, and heightened importance of configuration drift and deployment pipelines rather than bespoke code.
Speed to market and product agility
The shift to a cloud model dramatically elevated EQ Bank’s ability to deliver new features. “Ten years ago, we were releasing new features about every two months. Last year, we got that up to 30 every month, and this year, we peaked at 50 per month.”
Such velocity has implications for QA teams: regression testing must keep pace, automation coverage becomes critical, release windows shrink, and continuous monitoring becomes non-optional.
The bank is also using its platform to push boundaries in product innovation, including a fully digital business account for small business owners, including real-time payments and open banking readiness, as well as multi-currency money transfers via integration with a leading payments provider, Wise.
“Setting up the integration between Temenos Core Banking and Wise was very simple. We quickly and efficiently connected all the debit, credits and payment types needed… And we could do this without having to recode any APIs. Using the Temenos SaaS has made it easy for our teams to design, develop and launch new products.”
From a QA perspective, these examples highlight key themes: API-first design, plug-and-play fintech integrations, minimal custom code (reducing bespoke regression burden), and the need for testing across cross-product journeys such as deposits, FX, payments and reporting.
Operational resilience, scale and regulatory readiness
The cloud-SaaS environment also underpinned EQ Bank’s ability to handle growth and regulatory demands: “There was an immediate post-cloud growth in our customer base of 100% year-on-year, and 400% in transactions.”
The bank has sustained customer numbers increasing by 10-15 per cent each year and transactions by around 40 per cent. To support regulatory and operational reporting demands, EQ Bank introduced a near-real-time data access layer.
“The TDH-EQB Fabric is empowering EQ Bank with faster insights, improved system performance, and a more agile digital ecosystem, all crucial for enhancing the experience we give customers and meeting our regulatory obligations.”
For QA teams in financial services, this means an expanded testing scope: performance and scalability testing under elastic loads, data-pipeline integrity testing, regulatory-reporting compliance verification, and ensuring fraud and risk controls operate synchronously with high-volume flows:
“Fraud management and risk mitigation on those payments is another key area where we want to have really good controls and a good synchronous way of being able to decline or stop payments before we have issues with them.”
Interestingly, EQ Bank has explicitly tied its cloud strategy to sustainability: “Our ESG programme is an important part of our business. We aim to do as much as possible to reduce our carbon emissions, and a move to the cloud would help meet our goals.”
The bank added it is “very proud of how the cloud helps us to reduce our carbon footprint. We can monitor our cloud resource consumption closely, and ensure that we are using server configurations and processes that optimise performance and energy-efficiency.”
While QA teams may view this as peripheral, in many regulated financial services firms the tech stack must now support sustainability reporting, data-centre resource monitoring and potentially governance-risk-compliance frameworks. Testing workflows may need to include validation of telemetry, resource-usage dashboards and audit trails.
Implications for QA software testing teams
The EQ Bank case offers several takeaways. Testing needs to shift left: with feature releases rising to 30-50 per month, manual QA has to be replaced or augmented by robust automation, continuous integration and continuous delivery pipelines, and real-time monitoring. Performance and scalability become baseline.
The bank’s 400 per cent transaction growth post-cloud means QA must simulate high loads, elasticity, fail-over scenarios and cloud-bursting behaviour.
Minimal customisation changes the test surface: EQ Bank emphasised “minimal customisations” of the SaaS core, reducing bespoke code but increasing reliance on configuration and integration. QA teams must focus on integration regression, API contracts, and ecosystem dependencies rather than heavy bespoke logic.
Data-pipeline and regulatory testing is no longer “nice to have.” Real-time data hubs such as the TDH-EQB Fabric mean that QA must validate data correctness, freshness, archival versus live data separation, and reporting integrity.
Fraud, risk and security testing must be synchronous. With high volumes and digital-first journeys, QA must validate fraud controls under real-time conditions, ensure synchronous decline flows, and test latency under load.
Digital-only and API-first direct banking raises UX and functional QA expectations. With joint-account opening in a few clicks versus legacy branch visits, the QA function must cover full end-to-end journeys across web and mobile.
EQ Bank explained in its report that “we are always looking to react quickly to customer feedback and bring to market more innovative services. For example, we are creating frictionless digital journeys to allow users to open joint accounts in just a few clicks that would normally involve cumbersome paperwork and often a couple painful, in-person visits to a branch.”
Finally, sustainability and observability are rising QA dimensions. Monitoring cloud-resource consumption, audit-trail of configuration changes, telemetry dashboards, and performance metrics tied to ESG goals may fall increasingly under QA responsibility.
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Looking for more news on regulations and compliance requirements driving developments in software quality engineering at financial firms? Visit our dedicated Regulation & Compliance page here.
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