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Rethinking Test Automation in BFSI: A Playbook in the AI Era
Learn with AI
One of the key tasks of a finance/banking/insurance QA team is to ensure that defects never slip into production. Automation testing plays a critical role in accomplishing that task.
However, now that we have AI, the industry is changing. Fast.
Just automation testing is not enough. It should now be augmented by the capabilities of AI. When done right, AI-augmented automation testing is a game-changer for QA teams in finance firms.
Here's the playbook to help your team achieve exactly just that:
The challenges that BFSI is facing in QA
Here is what we observe to be happening in the BFSI QA world:
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Low automation coverage leads to prolonged test cycles and delayed releases.
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Inadequate test coverage definitions result in bugs slipping through both development and production stages.
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Manual regression testing remains tedious and time-consuming, slowing down time-to-market.
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Automation efforts struggle to keep up with the fast-paced customization of BFSI applications.
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Cloud migration introduces a need for a test automation platform that can handle infrastructure changes while reducing cost and operational friction for BFSI companies.
The human challenge of BFSI test automation
The BFSI industry doesn’t operate in isolation:
- Wage pressures are mounting
- The ongoing tech talent war is making it increasingly difficult, if not borderline impossible, to attract and retain highly skilled engineers.
As you rethink your test automation strategy, it's essential to account not just for rising costs, but for the very real challenge of staffing.
A more fundamental question looms: will you be able to find and keep the right people to build, modify, and maintain traditional test automation frameworks?
Most current tools, especially those that rely on recorders or frameworks tied to code, are heavily engineer-centric. Think: Playwright, Cypress, Selenium. They all require a lot of work to maintain.
That means you're not just solving for today’s engineering resources, but tomorrow’s as well. Ask yourself this: in three years, will you be able to hire a test automation engineer (or SDET) willing to debug flaky scripts written by someone who left two quarters ago?
That means BFSI companies need a new playbook, one that is made for the AI-driven world.
The QA playbook for BFSI
Here's what to do:
- Invest in AI. Recently Gartner released a Magic Quadrant report on the top AI testing tools that are making an impact. When implemented properly, a tool like TrueTest is really helpful when it can analyze production environment to then create, maintain, and execute regression tests based on real user behavior, freeing teams from the constant grind of manual test upkeep.
- Invest in low-code/no-code test automation. Test automation should empower every team member, not just those with deep technical expertise. Low-code/no-code platforms enable testers, product owners, and business analysts to participate in automation without needing to master programming.
- Invest in the people. Tools and technology create leverage, but people drive outcomes. Building a culture of quality requires continuous learning and open communication between developers and testers. When you give teams the training and trust to experiment with new tools and methods, that's when they grow the most.
Conclusion
The future of QA in BFSI industry is about evolving with it.
Traditional frameworks alone can no longer keep pace with today’s demands. As teams embrace AI, BFSI firms can start to truly build resilient, future-ready QA operations.
The industry is shifting fast, now’s the time to adapt.
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FAQs
What QA challenges are banks and financial institutions facing today?
BFSI QA teams struggle with low automation coverage, poorly defined test coverage that lets bugs slip into dev and production, slow and tedious manual regression testing, automation that can’t keep up with constant app customization, and cloud migration that demands more flexible, cost-efficient test platforms.
Why are traditional test automation frameworks not enough for BFSI anymore?
Traditional engineer-centric tools like Selenium, Playwright, and Cypress require heavy maintenance and specialized skills, which is hard to sustain amid wage pressure and tech talent shortages. As systems evolve and staff turns over, it becomes difficult to keep these fragile frameworks updated.
How can AI-augmented testing improve QA in BFSI companies?
AI-augmented tools like TrueTest can analyze production behavior to automatically create, maintain, and execute regression tests based on real user flows, reducing manual upkeep and helping BFSI teams prevent defects from reaching production more efficiently.
Why is low-code/no-code automation important for BFSI QA teams?
Low-code/no-code platforms allow testers, product owners, and business analysts—not just engineers—to participate in automation, reducing dependence on scarce coding talent and making the organization’s automation strategy more resilient over time.
What role do people and culture play in modern BFSI QA strategy?
Tools create leverage, but outcomes depend on people. Investing in training, continuous learning, and open communication between developers and testers helps build a culture of quality where teams can experiment with AI and new methods and grow with the industry’s rapid changes.
