Subset Sum Reconciliation Algorithm for Transaction Matching
Cointab’s subset sum reconciliation algorithm helps finance teams match grouped amounts across internal and external records. It is useful when one transaction on one side corresponds to multiple transactions on the other side, or when several entries need to be combined before the totals can be compared.
This capability is especially helpful in payment reconciliation, settlement reconciliation, bank reconciliation, vendor reconciliation, and any workflow where transaction-level detail does not always line up one-to-one.
What the subset sum reconciliation algorithm does
The subset sum reconciliation algorithm looks for combinations of records that add up to a target amount. In finance operations, that usually means comparing Side A records, which are your internal records, with Side B records, which come from banks, payment gateways, marketplaces, vendors, or other external systems.
Instead of reviewing rows manually in Excel, finance teams can use Cointab to:
- upload the required files
- map dates, amounts, and identifiers once
- run structured matching logic
- review fully matched, partially matched, unmatched, and skipped records
- download an audit-ready Excel report
This makes the matching process more consistent and easier to review during month-end close or audit preparation.
When subset sum matching is useful
Subset sum logic is useful when exact row-by-row matching is not enough. Common scenarios include:
- a single settlement covering multiple sales transactions
- one bank deposit covering multiple invoices or receipts
- one vendor payment offsetting several open invoices
- a refund or chargeback that needs to be grouped with related entries
- a delivery partner remittance that includes multiple orders or deductions
- a net amount on one side that must be compared against several gross or adjusted entries on the other side
It is also helpful when identifiers are incomplete, slightly different, or spread across multiple columns.
One-to-many and many-to-one matches
A subset sum reconciliation algorithm can support one-to-many and many-to-one matching where the combined total matters more than a single row match.
For example, a single settlement may correspond to multiple orders, or multiple receipts may combine into one bank entry.
Net-to-net and grouped amount matching
Some finance workflows require grouping before comparison. Cointab supports structured reconciliation logic for grouped amounts, partial matches, and contra-style scenarios where entries must be compared at the correct net value.
How Cointab uses subset sum logic
Cointab is designed as a flexible reconciliation engine, not just a simple spreadsheet replacement. The subset sum capability sits inside a broader workflow that finance teams can reuse across periods.
1. Upload your files
Users start by uploading CSV, XLS, or XLSX files for Side A and Side B. Supporting files can also be added when enrichment or lookup is needed.
2. Map the required fields
Users map the key fields needed for reconciliation, such as:
- transaction date
- amount
- order ID
- invoice number
- transaction reference
- bank UTR
- settlement ID
- AWB number
3. Apply matching logic
Cointab first applies structured reconciliation rules. The engine can compare exact values, subsets, grouped records, and related transactions. The subset sum approach helps identify combinations that total the expected amount.
4. Review open items
Once the structured matching run is complete, Cointab highlights the remaining open transactions. AI can then help analyze difficult exceptions, but weak matches are not forced into a match.
5. Handle manual exceptions
If the business context is known but the system cannot confidently match the records, users can manually match transactions when the totals tally. Manual matches remain clearly marked for audit visibility.
6. Export the report
Finance teams can download reconciliation reports that show matched, partially matched, unmatched, and skipped records. This helps with internal review, partner follow-up, and audit trails.
Finance use cases for subset sum reconciliation
Subset sum matching is valuable across several recurring finance workflows.
ECommerce sales vs payment gateway
When sales orders are paid in separate chunks, refunded, or combined with fees and adjustments, subset sum logic helps match the expected internal records with gateway settlements.
Marketplace sales vs settlement
Marketplace reconciliations often involve sales, commissions, deductions, returns, and settlement payouts. Grouped matching helps finance teams compare the right set of rows instead of relying on a single-line match.
Bank vs books
Bank reconciliation often involves grouped receipts, bulk deposits, payment batches, and timing differences. Subset sum logic can help isolate which entries belong together.
Vendor reconciliation
Vendor statements may combine invoices, credit notes, debit notes, and payments in ways that do not map cleanly to one line item. Grouped matching makes exception review simpler.
COD and logistics reconciliation
Cash collection and remittance workflows can include multiple deliveries, deductions, and settlement adjustments. Subset sum matching helps teams compare remittance totals against internal order data.
Why finance teams use this feature
Subset sum reconciliation is useful because it reduces manual spreadsheet work while keeping the process auditable.
Better exception handling
Instead of checking every row manually, finance teams can focus on the items that remain open after structured matching.
More consistent reviews
The same matching logic is applied every time, which helps avoid inconsistent Excel formulas or person-dependent review methods.
Reusable setup
Once a reconciliation is configured, the same workflow can be reused for future periods with the same mapping and logic.
Audit-ready reporting
Each run produces a clear reconciliation output that finance, audit, and operations teams can review later.
Works with recurring workflows
Cointab can be used for monthly, weekly, daily, or custom reconciliation cycles. This makes it suitable for recurring finance operations rather than one-off analysis.
How subset sum logic fits into the broader reconciliation workflow
Subset sum matching is most effective when it is part of a structured reconciliation process.
- Side A and Side B records are uploaded or received automatically.
- Required columns are mapped.
- Optional supporting data is used for enrichment or lookup.
- Derived columns can be created when amounts or identifiers need to be normalized.
- Structured reconciliation runs.
- Open transactions are analyzed further.
- Users review matched, partially matched, unmatched, and skipped items.
- Reports are downloaded or sent to downstream systems through email, SFTP, or API.
This gives finance teams a clearer view of what matched, what did not match, and what needs follow-up.
Built for audit-friendly finance operations
Cointab keeps reconciliation transparent. Finance users can see the files used, the fields mapped, the logic applied, and the final classification of transactions. That is important when teams need to explain differences to auditors, leadership, or external partners.
The result is a more controlled reconciliation process that supports financial close, exception management, and recurring reporting without relying on fragile spreadsheet work.
