Why QA in finance matters: trends, challenges and solutions

Imagine this: a banking app crashes mid-transaction, freezing a customer's funds. They call customer support — long wait times. Frustrated, they tweet about it. Within minutes, trust erodes, competitors gain an opportunity, and regulators take notice. 

Could this all have been prevented? Absolutely. 

In 2025, software quality assurance (QA) is a business imperative. The banking and fintech sectors process trillions annually (e.g., the U.S. ACH network alone handled $80 trillion in 2023), and even a minor glitch can cause millions in losses and reputational damage. 

As customer expectations, regulatory scrutiny, and cyber threats rise, financial firms must ensure seamless, secure, and high-performing software.  

But how?  

By embracing the latest QA trends, overcoming critical challenges, and implementing best-in-class testing strategies. 

Current trends in software testing for banking and fintech 

AI and automation in testing: The future is now 

Some companies manage to push out updates weekly without breaking a sweat. Others stumble. The difference often comes down to automation, and with the help of AI, it can be a game changer.  

A recent study showed that 68% of firms are using or piloting generative AI in testing. They are reducing test execution time by up to 72%. Additionally, the World Quality Report (WQR) 2024-25 respondents mentioned that AI helps attain better productivity (65%), boosted CX (41%), and less issues (29%).

AI and QA are working together to generate test cases, detect defects, quickly analyze the root cause of test failures, and adapt test scripts in real time.

This improves test coverage, cuts execution time, and allows QA engineers to focus on high-impact issues instead of routine checks. 

The most effective approaches combine automation with clear goals and human oversight. QA engineers use AI as a tool, not a replacement. This keeps quality at the center while speeding up delivery. 

And the benefits go beyond QA. According to IBM’s cost of a data breach 2024 report, organizations that extensively use security AI and automation save an average of $2.22 million in breach-related costs compared to companies not using AI and automation.

AI is improving early testing by flagging risks sooner, reducing rework, and uncovering edge cases that traditional methods might miss. 

Security testing: Can you afford a breach? 

Cybercrime is expected to cost the global economy $12 trillion in 2025. With financial institutions handling enormous volumes of sensitive data, they remain a top target for cybercriminals. Regulators are acting. Since January 2025, the EU’s Digital Operational Resilience Act (DORA) requires firms to regularly test their digital defenses to prove they can withstand real-world threats.

In the UK, the Operational Resilience Framework and the upcoming Cyber Security and Resilience Bill are raising the bar. Alongside these, global standards like ISO 27001 and ongoing GDPR requirements continue to shape expectations. 

With this in mind, it’s safe to say security testing should no longer be left until the end. It needs to be built into every stage of development. Approaches such as DevSecOps and Secure SDLC integrate security steps directly into development pipelines. Meanwhile, from traditional penetration tests to automated scanning and the emerging world of AI-powered testing, the tools are evolving, and so are the requirements. 

Effective security testing protects more than systems. It safeguards operations, brand reputation, and the trust of every customer. 

This blog post covers the top 5 questions to ask your QA provider to ensure they will help launch faultless and attack-proof IT solutions. 

Performance testing: Can your system handle the pressure? 

What happens when tens of thousands of users log in at once to pay bills, transfer funds, or place trades? Will your system stay responsive, or will it stall when it matters most? 

Performance is about reliability under pressure.

In finance, a delay of even one second can be enough to cause a failed transaction, trigger a compliance breach, or send users straight to a competitor. These aren’t hypothetical risks, they happen daily across the sector. 

Customers expect real-time services. They want balances to update instantly, payments to go through without lag, and trades to clear with no delays. If that experience breaks down during peak demand, it’s not just an inconvenience. It’s a warning sign. 

That’s why financial platforms run full-scale performance tests before launch. These simulations mimic real-world stress: surges in mobile traffic after payday, market volatility during earnings season, or coordinated attacks meant to overload systems. They measure how infrastructure holds up, where it slows down, and what breaks first. 

Blockchain technology testing: No second chances 

Testing blockchain systems is like walking a tightrope without a net. There’s no safety catch. No quick fix. If you get it right, you build the kind of trust users remember. Miss a step, and the fallout can be catastrophic. There is no undo button. 

The risk is built into how blockchain works. Once a smart contract goes live, you can’t update or patch it. Any mistake becomes permanent.

When Euler Finance was hacked in March 2023, attackers found a flaw in a recently updated contract and walked away with $197 million. 

Blockchain also brings its own challenges. Every transaction is permanent and replicated across a distributed network. If a node drops out, if latency spikes, or if the chain forks, systems must respond predictably. QA teams need to test under stress, simulate slowdowns, and verify that consensus mechanisms hold. 

Attackers are adapting too. As more services shift to decentralized apps, the entry points multiply. Permissions, transaction limits, and protocol logic all become targets. Testing has to cover these paths, challenge assumptions, and surface edge cases before they’re exploited. 

On a tightrope, the margin for error is zero. That's the level blockchain testing demands. 

Cloud testing: Scale smart without slipping on security 

Cloud solutions have changed how banks and fintech companies build and deliver software and ecosystems. Teams test faster, deploy globally, and scale without building their own infrastructure. But with that flexibility comes new risks. QA needs to evolve alongside it. 

Performance is a top concern. Financial platforms must remain responsive even during peak demand. Cloud-based testing needs to simulate traffic spikes, increased loads, and delays between regions. The goal is to detect bottlenecks before users notice them and ensure smooth performance across geographies. 

Security is just as important. Sensitive data often moves through third-party infrastructure. Testing must verify encryption, access controls, and system behavior under attempted breaches.

Many incidents in cloud environments come down to simple misconfigurations or gaps in identity checks. 

Resource use also matters. Too much capacity wastes money. Too little causes crashes. Testing helps teams find the balance by observing how real workloads interact with computing power and storage. 

In the cloud, speed and scale are easy to promise. It’s keeping them reliable that takes serious testing. 

Challenges and solutions in software testing for banking and fintech 

Limited resources and tight budgets 

Financial institutions face high expectations but often work with lean teams and strict budgets. With limited manpower and funding, manual testing can become a serious bottleneck. When teams are stretched thin, there is a risk that critical areas may be under-tested, which can lead to delays or even software failures that affect customer trust. 

One way to address this is by integrating automated testing.

Automation streamlines routine tasks and speeds up test cycles. Though this may increase the budget in the short term, over the life of a project implementation should pay for itself and start saving  money.

It allows teams to run large volumes of tests quickly and consistently, freeing testers to focus on high-risk or complex areas.

This is also when collaborating with external testers becomes invaluable to address resource shortages.

Within several days, outsourced QA vendors can provide the additional support needed during peak periods, ensuring that testing remains thorough without requiring long-term increases in staffing and reducing training costs. 

Complexity of modern financial systems 

Modern banking platforms are built on a mix of legacy systems, modern applications, APIs, and third-party services. This blend creates intricate environments where different systems interact in unexpected ways. A small change in one component can trigger issues elsewhere, making comprehensive testing a significant challenge. 

Automated integration testing as part of regression testing can also play a crucial role in these environments. By simulating real-world scenarios, automated tests help catch issues across interconnected systems early in the development cycle.

This approach not only saves time but also ensures that all components work together as intended.

This is also another case when partnering with external testers may be effective. These specialists bring fresh perspectives, domain expertise and advanced testing methodologies that can help manage the complexity, identify hidden dependencies, and ensure that every part of the system is scrutinized. 

Regulatory requirements 

As mentioned previously, financial software must comply with a host of ever-changing regulations, such as GDPR, PSD2, and DORA.

Read about the role of QA teams ensuring compliance with DORA’s stringent regulations here in our blog.

These standards are designed to protect customer data and ensure system integrity, and they add another layer of complexity to the QA process.

Failing to meet regulatory standards can lead to significant fines, legal issues, and loss of customer confidence. 

There are three approaches you can use, either on their own or as part of a larger system: 

• Set up automated testing to run routine compliance checks. This way, every release meets the required standards without extra manual work.  

• Bring in external teams with regulatory expertise. They can offer valuable support setting up testing processes and keeping your compliance strong as standards change.  

• Invest in continuous learning and team development. Keeping your staff up to date ensures they are always ready to adapt. 

When you combine these strategies, you create a flexible framework that not only meets current regulatory demands but also adjusts easily for future changes.   

How a1qa helped a client 

A US-based investment portfolio management ecosystem, offering subscription-based IT products for financial advisors and individual investors, partnered with a1qa to boost software quality and avoid costly post-release fixes. The client’s solutions included a B2B platform (with a website, API, and test console), desktop systems, a B2C platform, and mobile apps. a1qa supported the project from the idea stage through to release, ensuring accurate financial data and reliable performance. 

Key QA initiatives included: 

Functional testing: 

• Verification of calculation formulas to ensure accuracy in research statistics. 

• Testing of embedded HTML/JS views and API data transfers for correct information display. 

Test automation: 

• Implementation of an image-based automation strategy  

• Introduced a console for checking changing data that performed nightly tests by scanning screenshots. 

• Introduction of C#-based test automation to verify huge scope of calculation activities. 

Mobile apps testing: 

• Execution of cross-browser and cross-device tests to guarantee consistent performance across different devices used globally. 

Integration testing: 

• Ensuring a consistent data format and successful transfer of all necessary information from various broker sites for both B2B and B2C solutions. 

Big data testing: 

The team ensured the validity, reliability, precision, integrity, and timeliness of data sets (global stock exchange trading statistics, currency cross rates, financial market news, etc.) obtained from various providers. When switching to a new information vendor the team conducted the migration and performed migration testing to ensure all the information remained intact. 

By integrating these QA practices early in the development cycle, the client reduced the feature lifecycle to two weeks. This proactive approach minimized the risk of critical defects and prevented expensive fixes after launch. 

a1qa’s involvement led to: 

• Shortened time to market and feature life cycle due to streamlined QA workflows. 

• Enhanced software quality with improved data consistency and a significant reduction in code smells. 

• Fewer customer support issues as cases of incorrect financial data were minimized. 

The project highlighted the importance of embedding QA processes from the start. 

Wrapping up 

The future of QA is exciting. Imagine using AI tools that not only spot bugs before they become problems but also generate test cases on the fly. Picture security testing that adapts in real time to catch emerging threats and performance tests that simulate real-world pressures with smart cloud setups.

Even blockchain testing is stepping up its game to ensure every smart contract is rock solid before launch. Embracing these innovations means QA teams do more than just fix issues. They prevent them, build trust, and keep everything running smoothly. 

Reach out to our experts if you want to explore QA options for your fintech software.