Amazon Payment Reconciliation Software for Finance Teams

Amazon payment reconciliation is often more than comparing a sales report with a payout file. Finance teams also need to account for fees, returns, reimbursements, deductions, settlement timing, and bank postings. Cointab helps teams handle this in a structured workflow by comparing Side A records from the business with Side B records from Amazon and related source systems.

Instead of rebuilding Excel formulas for every period, users can map fields once, run reconciliation, review exceptions, and export audit-ready reports. The same setup can be reused for future Amazon periods, which makes recurring reconciliation faster and easier to control.

How Amazon payment reconciliation works in Cointab

Cointab treats Amazon reconciliation as a Side A and Side B comparison:

• Side A is the business record set, such as order data, internal sales reports, ERP exports, ledger entries, or expected receivables.
• Side B is the Amazon record set, such as Merchant Transaction Reports, disbursement files, settlement reports, return reports, or bank statement entries.

A typical workflow looks like this:

1. Upload the required Amazon and internal files.
2. Map date, amount, and identifier columns.
3. Add supporting files where needed for lookups or enrichment.
4. Create derived columns if a value needs cleaning, combining, or calculation.
5. Run reconciliation manually or on a schedule.
6. Review matched, partially matched, unmatched, and skipped transactions.
7. Download the Excel reconciliation report or send the output to another system.

Data commonly used for Amazon reconciliation

Amazon reconciliation can involve several reports, depending on the workflow being reviewed. Common inputs include:

• Internal sales or order report
• Merchant Transaction Report
• Amazon disbursement report
• Settlement report
• Returns report
• Reimbursement report
• Bank statement
• SKU master or product master
• Fee or rate card file
• Supporting reference data for lookups and enrichment

Cointab supports CSV, XLS, and XLSX files. For each primary report, users can define the header row and map fields such as:

• Transaction date
• Amount
• Order ID
• Transaction ID
• Settlement ID
• Reference number
• Invoice number
• Bank UTR
• SKU or product code

If a file does not follow the configured structure, the system can reject it with a clear error so the reconciliation remains controlled and auditable.

What finance teams check during Amazon payment reconciliation

Amazon sellers and finance teams usually need to review more than just final payout amounts. Common checks include:

• Order-level payment matching to compare expected sales with reported payments
• Fee verification to review shipping, referral, closing, or other deductions where applicable
• Settlement reconciliation to compare Amazon disbursements with bank credits
• Return and refund impact to see where amounts were reversed or adjusted
• Timing differences to identify payments that are pending rather than missing
• Exception review to isolate amounts that do not match cleanly

Cointab separates fully matched, partially matched, unmatched, and skipped records so teams can focus on exceptions instead of reviewing every row manually.

Matching logic for complex Amazon records

Amazon reconciliation does not always follow a simple one-to-one match. A single order may map to multiple entries, or several entries may need to be grouped before they can be compared.

Cointab supports structured matching scenarios such as:

• One-to-one matching
• One-to-many matching
• Many-to-one matching
• Many-to-many matching
• Net-to-net comparison
• Partial matching
• Contra-style matching where relevant

Matching can use identifiers such as order IDs, transaction IDs, settlement IDs, UTRs, or other business references. It can also use comparison logic such as equals, contains, similar, and subset-based matching.

This is useful when Amazon data appears across multiple files or when internal records and partner reports do not use the same naming or reference format.

AI support for difficult open items

After the structured matching engine runs, Cointab can use AI to help review remaining open transactions. This is useful when references are incomplete, descriptions vary, or the reason for the difference is not obvious from rules alone.

AI can help with:

• Creating derived columns from plain-language instructions
• Reviewing open transactions for likely causes
• Identifying whether a missing file may be the reason for an exception
• Suggesting whether a refund, return, fee, or timing difference may explain a mismatch

AI remains reviewable and conservative. If the evidence is not strong enough, the transaction stays open rather than being matched weakly.

Derived columns and supporting data

Amazon reconciliation often becomes easier when users can prepare the data before matching. Cointab supports supporting datasets and derived columns for this purpose.

Examples include:

• Cleaning order IDs or transaction references
• Combining fields into a single identifier
• Calculating net amount after deductions
• Converting refund amounts into negative values
• Looking up fee rates from a rate card
• Adding missing product, SKU, or delivery details

Users can describe the calculation in natural language, and Cointab can generate an Excel-style formula to create the derived column.

Reconciliation reports and dashboard visibility

Once reconciliation is complete, users can review a report dashboard that shows:

• Total summary
• Fully matched records
• Partially matched records
• Unmatched records
• Skipped records
• Transaction-level tables
• Filters for deeper analysis
• Manual match options where needed
• Excel export for audit and follow-up

The dashboard keeps reconciliation history available for future reference, which helps teams support month-end close, partner follow-up, and audit preparation.

Automation for recurring Amazon workflows

Amazon reconciliation is usually recurring, not one-time. Cointab supports reusable workflows so teams can set up the reconciliation once and run it again for future periods.

Automation options include:

• Manual upload
• Email-based file intake
• SFTP-based file intake
• API-based file intake
• Scheduled reconciliation runs
• Automated output delivery through email, SFTP, or API

This makes it possible to reduce repetitive upload work and keep internal finance, accounting, analytics, or BI systems updated with reconciliation output.

Why Amazon reconciliation needs a structured approach

A spreadsheet-only approach can work for small files, but it becomes difficult when the business has multiple reports, recurring payouts, fee deductions, or open items that carry across periods. A structured reconciliation workflow gives finance teams more control over what matched, what did not match, and what needs follow-up.

For Amazon-facing finance teams, that means less manual comparison work, clearer exception handling, and a more consistent report trail across periods.

FAQ

What data do I need for Amazon payment reconciliation?

The exact files depend on the workflow, but most teams reconcile internal sales or order data against Amazon transaction, disbursement, settlement, return, and bank statement files. Supporting files such as SKU masters or fee rate cards can also help.

Can Cointab handle Amazon fees and deductions?

Yes. Amazon reconciliation workflows can include fee verification and deduction review, along with settlement and bank matching. Supporting data and derived columns can help calculate expected values more clearly.

Can recurring Amazon reconciliation be automated?

Yes. Once a reconciliation is configured, it can be reused for future periods and automated through email, SFTP, or API-based data flow. Scheduled runs are also supported.

What happens to transactions that do not match?

Cointab separates partially matched, unmatched, and skipped records so finance teams can review exceptions in a controlled way. Users can also manually match items where the business context supports it.

Can missed files be added later?

Yes. If a file was missed, it can be uploaded under the same reconciliation and the report can be refreshed so the workflow reflects the complete data set.