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- Test the payment schedule after an order is placed
Test the payment schedule after an order is placed
Place the order, open the app, and check the outstanding balance and the paid and scheduled badges are consistent with each other.
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Once a buy now pay later order exists, the shopper manages it somewhere else: an app or a portal showing what has been paid and what is still coming. That surface is where the numbers have to stay consistent over weeks.
This use case places an order on the Klarnah checkout and then checks the schedule it produced.
The flow under test
The outstanding balance is a derived figure, and deriving it wrongly is easy when one payment has already been taken.
- Order total - $180.00, the full value of the purchase.
- Outstanding - $135.00, which is the total less the payment taken at checkout.
- Payment one - $45.00, marked paid.
- Payment two - $45.00, marked scheduled rather than paid or overdue.
Asserting the badges alongside the amounts is what makes the balance verifiable. An outstanding figure of $135.00 with all four payments marked scheduled is arithmetically consistent and factually wrong.
Note: The setup is compressed into one step because the order is not the subject of this test, which keeps the three schedule assertions separately attributable. Start on TestMu AI. Start for free
The test file
The step ceiling is raised to 50 here, since the flow has to complete a full checkout before it reaches the surface it is actually testing.
---
mode: testing
url: https://my-testing-repo-main.vercel.app/klarna-clone-app/checkout?reset=true
max_steps: 50
tags: [klarna, payments, bnpl]
---
# Klarnah 14.3: Payment schedule
Catalog objective: verify the placed order appears with its payment schedule.
Key assertion: the first instalment date and amount are correct.
## Place the order
Type "Priya Nair" into "Full name", type "4417" into "Last 4 of ID number", click "Continue with Klarnah", then click "Confirm and pay $45.00 today".
## Open the Klarnah app
Click "Open it in the Klarnah app" and verify the order card title reads "Studio Lamps · KL-3301".
## Verify the balances
Verify "Order total" reads "$180.00" and "Outstanding" reads "$135.00".
## Verify the first instalment
Verify the schedule table shows Payment 1 of 4 due "2026-09-15" at "$45.00" with a "Paid" badge, and Payment 2 of 4 due "2026-09-29" at "$45.00" with a "Scheduled" badge.The order card is identified by both the product and the order reference, so the app opening on a different order fails immediately rather than producing confusing balance mismatches.
Step by step coverage
One setup step and three assertions, which is the right shape for a post-purchase flow.
| Step | What it proves |
|---|---|
| Place the order | A real order exists with a first payment already taken |
| Open the Klarnah app | The management surface opens on the correct order |
| Verify the balances | Order total and outstanding are both correct and consistent |
| Verify the first instalment | Payment one is paid, payment two is scheduled, both at the right date and amount |
A third of this run is setup. That is the normal price of testing anything post-purchase, and the strongest argument for automating it rather than clicking through a checkout by hand every time.
Running it
kane-cli testmd run tests/klarna/payment-schedule_test.mdOnce the flow runs, the same file covers the schedule after any change to how instalments are generated.
Setup-heavy flows are the ones worth running unattended. Running flows asynchronously covers not waiting on them, and the test.md format covers the step ceiling used here.
Author
Bhawana is a Community Evangelist at TestMu AI with over 3 years of experience creating technically accurate, strategy-driven content in software testing. She has authored 50+ blogs on test automation, cross-browser testing, mobile testing, and real device testing. She also serves as Product Marketing Manager for Kane CLI, the command-line tool that runs browser automation from the terminal using natural-language flows in a real Chrome browser. Bhawana is certified in KaneAI, Selenium, Appium, Playwright, and Cypress, reflecting her hands-on knowledge of modern automation practices. On LinkedIn, she is followed by 6000+ QA engineers, testers, AI automation testers, and tech leaders.
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