Returns are a normal part of running a Lazada store—but they can quietly throw your books off balance if they’re not tracked properly. Between refunds, restocked items, and platform deductions, it’s easy for finance data to get messy fast. For SMEs selling on Lazada, clean accounting means knowing exactly when a return affects revenue—and when it doesn’t.
Here’s how successful online sellers are keeping their books accurate and audit-ready using ccMonet.
A return affects multiple parts of your accounting flow:
This means your sales report, payout statement, and bank record won’t align—leading to understated or overstated revenue if handled manually.
With ccMonet, you can upload your Lazada payout and transaction reports directly.
AI automatically detects and links refund entries back to their original sales transactions—whether the return happened the same week or later.
It categorises each case clearly:
This automation eliminates hours of manual matching between reports.
In manual accounting, sellers sometimes post refunds as expenses rather than negative sales—making profitability look worse than it is.
ccMonet records returns correctly as sales adjustments, ensuring:
When Lazada deposits funds, the amount already includes multiple deductions and refunds.
ccMonet’s AI reconciliation matches each payout to the corresponding transactions, identifying:
This ensures your cash ledger matches Lazada’s actual activity.
Once reconciled, ccMonet’s AI Insights dashboard shows:
You get a transparent view of how returns impact your margins—and how your refund ratio compares over time.
Each return and adjustment is timestamped, categorised, and traceable back to its original order ID.
For Singapore sellers registered for GST, this ensures refund credits are accounted for correctly—no guesswork, no missing documentation.
Sell confidently, reconcile automatically.
With ccMonet, Lazada sellers can track returns, refunds, and fees in real time—keeping their financial records clean, compliant, and completely aligned with platform data.
Because clean books shouldn’t depend on perfect spreadsheets—they should depend on smart automation.