How Bajaj Finserv Cut Test Execution Time by 70% and Brought Escaped Defects Below 3%

As one of Asia’s largest NBFCs, Bajaj Finserv has built a large digital financial ecosystem spanning lending, asset management, wealth management, and insurance. With 24 products across 12 lines, the organization serves 40 million mobile users and generates 2.5 million monthly website sessions.

And being in a highly regulated fintech environment, delivering consistent performance across platforms is a high priority, but as digital adoption grew, testing infrastructure struggled.

With local-first setups, limited parallel execution, and no scalable infrastructure, release cycles slowed at exactly the moment the business needed them to move faster, making it harder to maintain high-quality digital experiences at scale.

For a Regulated NBFC, the In-House Test Infrastructure Was Holding Back Release Velocity

"It’s a consumer website, consumer app. Most things are changing on a daily basis. So it’s always a catch-up game for us," says Abhijeet. For Bajaj Finserv's QA team, that catch-up game had a structural problem. Development timelines regularly ran over.

Development moved fast. Testing had to absorb whatever was left. QA team against a product that shipped continuously, with timelines that kept shrinking from both ends. Development ran over. Testing got compressed. What started as a full testing window became half. Sometimes less.

"In a scenario where two weeks of testing get compressed to one, the tools weren’t there to deliver a compliance sign-off within the timeline," says Abhijeet.

On a platform serving millions of consumers across loans, insurance, and payments, a broken CTA or a 404 redirect is not a minor bug. It is a visible failure on a platform people use to manage their financial lives. For a regulated NBFC, there is no tolerance for that.

Moving to Cloud Execution Reduced The Automation Runtime from 8 Hours to 2

The root constraint was infrastructure. Bajaj Finserv's automation suite existed, but it ran locally, sequentially, and without any mechanism for parallel execution. A full regression cycle took 8 hours.

"Time to market matters a lot. It’s a consumer-facing website and app," says Abhijeet.

When Bajaj Finserv evaluated testing platforms, two requirements were non-negotiable.

• First: Cross-browser testing across multiple environments at speed
• Second: Parallel CI/CD execution for faster results and release decisions

"The execution time we got using HyperExecute, that’s the major differentiator," says Abhijeet.

The integration was direct. HyperExecute was plugged in as a runner inside Bajaj Finserv's Azure Pipelines workflow. The existing Selenium-based suite was re-pointed to the cloud.

Previously, it was taking 8 hours to execute our automation suite for sanity, regression, or anything during the hot fixes or production deployment. Right now it's taking around 2 hours only. That's a 70% reduction in timeline.

Abhijeet TewareHead of QA, Bajaj Finserv

For a product team running seasonal campaigns on tight go-live schedules, that compression changes what is possible. Sign-offs that previously couldn't be made in time can now be made with actual test data behind them.

Better Debugging Visibility Cut Test Maintenance from 60% to 50%

Before HyperExecute, the team had no visibility into failures during a run. When a test broke, engineers reproduced the failure manually on local machines. There were no logs tied to individual test runs, and no video of the execution state at the point of failure.

Two capabilities changed this:

• Test-level logs allow engineers to pinpoint exactly where a failure occurred without a manual reproduction cycle. The failure is visible, the context is preserved, and triage starts immediately.
• Video capture during execution changed how the team understands failures altogether. Rather than hypothesizing what went wrong, they watch it. "The feature we are using religiously is the video capturing capability during execution," adds Abhijeet.

Together, these features significantly reduced time spent on failures and test maintenance, resulting in a 17% reduction in test maintenance.

"The maintenance-to-build ratio has shifted from 60% maintenance / 40% build to 50/50," explains Abhijeet.

Broader Coverage, Yet Fewer Escapes to Production

For three years, Bajaj Finserv had held an escaped defect rate of under 5% as a hard KPI. Since adopting TestMu AI, that number has dropped below 3%, a 40% reduction.

What makes that number more significant is how it was achieved. The team did not grow. The same 48 engineers, supporting the same consumer platform, covering more ground than before. Test coverage moved from 60% to 83%, a 38% increase.

On a platform serving crores of consumers, every escaped defect is a failed loan application or a broken payment flow made public. For a regulated NBFC, that is not a quality metric. It is a reputational one.

What's Next

Bajaj Finserv did not hire more engineers to solve a quality problem. They fixed the constraint that was holding the existing team back. Local infrastructure became cloud execution. Sequential runs became parallel. Eight hours became two.

Everything else followed. Coverage expanded because there was finally time to run more tests. Defects stopped escaping because more of the product was covered. The maintenance burden eased because failures were visible the moment they happened.

For a platform serving crores of consumers across loans, insurance, and payments, quality is not a back-office function. It is what the brand runs on. And for the first time, the infrastructure matched the ambition.

Ready to improve your testing? Schedule a demo to see how TestMu AI can help your team achieve similar results.