Automate Data Preparation Before You Reconcile

Data preparation is one of the most time-consuming parts of reconciliation. Finance teams often spend hours cleaning files, fixing formats, removing duplicates, and aligning column names before they can even start matching transactions.

Cointab helps automate that preparation step so teams can move from raw files to reconciliation faster. Instead of rebuilding the same Excel logic every period, users can upload data, map fields once, enrich records with supporting files, create derived columns, and run a structured reconciliation workflow that is easy to review and reuse.

Why data preparation slows reconciliation

Before matching can begin, finance teams usually need to combine data from different systems such as ERP exports, bank statements, payment gateway reports, marketplace settlements, vendor statements, or internal sales files. These files often come in different formats and levels of detail.

Common preparation challenges include:

• Different column names for the same field
• Missing dates, amounts, or reference numbers
• Duplicate rows and repeated transactions
• Inconsistent formats across monthly files
• Partner data that does not match internal identifiers
• Manual VLOOKUPs and formulas that are hard to audit
• Large files that become difficult to manage in Excel

When data preparation is manual, reconciliation becomes slower and more error-prone. Teams may spend more time preparing the data than actually reviewing exceptions.

How Cointab automates data preparation

Cointab is designed to help finance teams prepare and reconcile data in one workflow. The platform follows a clear Side A and Side B model:

• Side A contains your internal records, such as sales, books, ledgers, or order data
• Side B contains external records from banks, payment gateways, marketplaces, delivery partners, vendors, or other sources

Users upload CSV, XLS, or XLSX files, select the required fields, and configure the reconciliation once. For recurring workflows, the same setup can be reused in future periods.

1. Upload files and map required fields

For each primary report, users map the key fields needed for reconciliation, such as:

• Date
• Amount
• Identifier or reference column
• Multiple identifiers where needed

This makes it easier to prepare standardised inputs for transaction matching, even when source files are not in the same format.

2. Use supporting data to enrich records

Sometimes the main reconciliation files are not enough. Teams may need lookup files such as product masters, order metadata, fee rate files, tax mappings, SKU mapping, or delivery partner reference data.

Cointab supports optional supporting data to help:

• Fill missing order details
• Merge related reports
• Add AWB or transaction references
• Pull in tax, fee, or status information
• Prepare data for matching without changing the source files manually

3. Create derived columns with AI assistance

Many reconciliation workflows require calculated fields, such as net amount, cleaned identifiers, or amount after fee. Cointab lets users create derived columns using Excel-style formulas, and AI can help generate those formulas from a simple prompt.

Examples include:

• Clean Order ID
• Net Amount
• Refund Amount as Negative
• Normalized Transaction ID
• Delivered Payment Amount

This reduces the need for manual spreadsheet work and helps standardize logic across runs.

4. Validate file structure before reconciliation

If a file does not match the configured format, Cointab can reject it with a clear error message so users know what needs to be fixed. This helps prevent bad inputs from entering the reconciliation process and keeps the workflow transparent.

What a better preparation workflow looks like

A strong reconciliation preparation process should help finance teams do four things well:

1. Standardize incoming data
2. Improve the quality of identifiers and amounts
3. Prepare files for structured matching
4. Keep the process reusable for the next run

Cointab supports this by turning data preparation into a configured workflow instead of a recurring manual task.

How prepared data improves reconciliation

Once the data is mapped and cleaned, Cointab runs structured matching across transactions. The reconciliation engine can handle common finance scenarios such as:

• One-to-one matches
• One-to-many and many-to-one matches
• Net-to-net reconciliation
• Contra matching
• Partial matches
• Cross-side matching with identifiers in different fields

After structured matching, remaining open items can be reviewed using AI-assisted analysis where appropriate. The goal is to help finance teams focus on exceptions instead of reviewing every row manually.

The report separates records into clear categories:

• Fully matched
• Partially matched
• Unmatched
• Skipped

This makes it easier to understand what matched, what needs review, and what was excluded because of invalid or incomplete data.

Why finance teams benefit from automated preparation

Automating data preparation supports day-to-day finance operations in several ways:

• Less manual cleanup: Teams spend less time fixing files before reconciliation
• More consistent inputs: The same mapping and preparation rules are reused every period
• Better auditability: Rules, fields, and outputs remain visible and reviewable
• Faster exception review: Open items are easier to isolate after standardized preparation
• Reusable setup: Once configured, the workflow can be used again for future runs
• Better coordination: Teams work in one shared workspace instead of passing spreadsheets around

For recurring workflows, Cointab can also automate data flow through email, SFTP, or API. That means preparation can become part of a scheduled reconciliation process instead of a manual monthly task.

Examples of where automated data preparation helps

Bank vs Books reconciliation

A finance team uploads bank statements and ledger data. Supporting files can help clean references, align payment descriptions, and match receipts and payments more efficiently.

Sales vs Payment Gateway reconciliation

An eCommerce team uploads internal sales data and payment gateway reports. Derived columns can clean order IDs, standardize amounts, and identify mismatches caused by refunds, deductions, or partial settlements.

Marketplace reconciliation

Brands working across marketplaces often receive settlement, returns, and deductions data in different files. Automated preparation helps combine those inputs before matching sales and settlements.

Vendor reconciliation

AP teams can prepare vendor ledger data and vendor statements for comparison, while keeping invoices, payments, and credit notes organized in a reusable format.

Built for recurring finance workflows

Data preparation should not be a one-off project. In most finance teams, the same reconciliation repeats every day, week, or month with new files.

Cointab is built so users can:

• Reuse the same reconciliation setup
• Run reconciliation for a new period
• Upload a missed file later and refresh the report
• Review history from the dashboard
• Automate recurring runs where needed

That helps teams reduce repetitive spreadsheet work and keep reconciliation outputs available for review and audit readiness.

A practical way to reduce Excel dependency

Excel remains useful, but it is often the reason reconciliation preparation becomes slow and difficult to maintain. Formula-heavy files can be hard to audit, hard to standardize, and hard to reuse across teams.

Cointab replaces that fragile workflow with a structured process where finance users can upload data, prepare it once, and keep the logic visible. The result is a more reliable reconciliation process with less manual intervention and clearer exception handling.

Frequently asked questions

What is automated data preparation in reconciliation?

Automated data preparation is the process of standardizing, validating, and organizing reconciliation files before matching begins. It reduces manual cleanup and makes it easier to compare Side A and Side B records.

What types of files can be prepared in Cointab?

Cointab supports CSV, XLS, and XLSX files. Teams can use internal reports, bank statements, payment gateway files, marketplace settlements, vendor statements, and other finance data sources.

Can supporting files be used during preparation?

Yes. Supporting data can be uploaded to enrich or complete the primary reconciliation data. It is useful for lookups, mappings, calculations, and merging related records before reconciliation.

Does Cointab support recurring reconciliation workflows?

Yes. Once a reconciliation is configured, the same setup can be reused for future periods. Teams can also automate data receipt and scheduled runs using email, SFTP, or API.

What happens to unmatched or skipped records?

Cointab keeps unmatched, partially matched, and skipped records visible in the reconciliation report so finance teams can review exceptions and understand why some records were not matched.