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Home / Solutions / Fintech SOLUTIONS · FINTECH

Fintech app testing with an audit trail

Correctness you can show the auditor. In fintech, "it probably works" is not a QA result. TestAutomate grades every run pass, fail, or blocked — with screenshot evidence attached — and runs on infrastructure you control, with an AI data path you choose.

Start free — no card →Read the security page
WHY FINTECH QA IS DIFFERENT

Your test results are records, not vibes

When money moves through your UI, three things change about testing: evidence matters, false alarms are expensive, and where the data flows is a compliance question. TestAutomate was built with all three in mind.

DEMAND 01

Evidence, not assertions

Every verdict ships with screenshots of what the agent saw at each step. When a balance displays wrong or a statement omits a line, you have the picture — not a log line that says "expect(true)".

DEMAND 02

No crying wolf

Every failure is re-driven by a stronger model before it reaches you. Runs that pass on retry are labeled flakes. When TestAutomate says fail, someone should look — that's the bar.

DEMAND 03

Environment honesty

A dead staging environment grades blocked, never failed. Your quality history says what actually broke in the product — which is exactly what a reviewer will ask for.

VERDICT RIGOR

Three states, strictly separated

  • Pass. The verifier confirmed the expected behavior, with the screenshots to prove it.
  • Fail. Reproduced by a stronger model on escalation before being reported. Ready to file — deduped, confirm-gated, evidence attached to the Jira issue.
  • Blocked. The environment prevented the test — outage, expired sandbox, broken fixture. Counted separately so product-quality metrics stay clean.
  • Advisory. UI changed but behavior is equivalent — a flag for a human, not a red mark on the record.

How grading works →

DATA PATH & DEPLOYMENT

Built for the security review

We won't wave compliance acronyms we haven't earned. What we will do is hand your security team an architecture that's easy to say yes to.

Self-hosted, fullyThe whole stack runs on your infrastructure — Node and Postgres, nothing exotic. Test data, run history, and evidence never have to leave your network.
BYOK model trafficBring your own AI key — Anthropic, Bedrock, Gemini, or Groq. Model traffic flows on your key, under your existing provider agreement, at provider cost with live meters and hard ceilings.
Credentials encryptedTest credentials are stored AES-256-GCM encrypted. The agent uses your real browser for real sessions — it works behind VPN and SSO without punching holes for a cloud runner.
Multi-tenant isolationWorkspaces are isolated per tenant, so separate teams, environments, and clients keep separate data.
Readable artifactsTests are portable, human-readable YAML. Reviewers can read exactly what runs — no opaque recorded blobs.
Spend governanceHard budget ceilings stop a runaway run before it becomes a finance question. Every dollar of model spend is metered and attributable.
Full security details →
SPRINT VERIFICATION

Every "fixed" ticket, independently re-verified

Point TestAutomate at your Jira board and each done ticket gets a bounded agent run with its own verdict and evidence trail. Re-fixes are re-verified. The sprint report is one line your risk committee can actually read: "12 tickets · 10 verified fixed · 2 reproduce · $4.87 model spend." The Jira workflow →

QA that stands up to the questions fintech gets asked

Self-host it, bring your own key, and keep the evidence. Ten design-partner spots open.

Start free — no cardTalk to the founders

Further reading

How a Test Run Gets Graded, Step by StepFollow one test run through TestAutomate's grading pipeline, from setup gate to recorded trajectory to a passed, failed, skipped, or blocked verdict.LLM as a Judge Software Testing in PracticeLLM as a judge software testing, from the QA side: why the judge must be separate and skeptical, where bias creeps in, and when deterministic checks win.Assumption Flags: UI Changed, Nothing BrokeAssumption flags mark runs where the UI differed from the test's wording but still met the intent. The run passes with a note for a human, not a failure.