Reconciliation Configurations – Key Concepts

Reconciling data across different systems, providers, and formats has always been a challenge. At BoxPay, we built BoxPay Reconciliations as a generic, flexible, and scalable reconciliation engine that can work with almost any kind of data. To make the most of it, let’s walk through the core concepts that power the system.

🔑 Recon Name

Every reconciliation setup starts with a Recon Name. Think of it as a unique identifier for a reconciliation process. For example:

• Bank vs. PG Settlement Recon
• Vendor Invoice vs. OMS Orders Recon

What makes BoxPay powerful is that you can create multiple reconciliations under a single account.

👉 For example, one merchant could have:

• Recon #1: Bank vs. Payment Gateway
• Recon #2: Payment Gateway vs. Ledger
• Recon #3: OMS Orders vs. Vendor Invoices

This flexibility allows businesses to manage all their reconciliation processes in one place, under one account.

📂 File Types

Each reconciliation involves comparing two sides. These sides are called File Types. Examples include:

• Bank Statement
• Payment Gateway (PG) Data
• Vendor Invoices
• Order Management System (OMS) Data

A File Type represents a source of truth in your reconciliation journey.

🗂️ File Sets

Within a File Type, you may have multiple File Sets to handle variations in file formats from different providers.

For example, under Bank Statements you may have:

• ICICI Statement (CSV)
• HDFC Statement (PDF)
• Axis Statement (XLSX)

This flexibility ensures you can plug in files from any source without breaking the reconciliation logic.

🔍 Matching Parameter

At the heart of reconciliation lies the Matching Parameter.

This is the unique rule that tells the system how to line up records across the two File Types.

Examples:

• Match records by invoiceId
• Match records using a combination of orderId + vendorId

BoxPay allows you to set matching logic that fits your exact business requirements.

💰 Recon Value

The Recon Value is the amount or metric being reconciled across files.

For example:

• Comparing transactionAmount in PG Data with creditAmount in Bank Statement.

This ensures not only records align, but also the value integrity is maintained.

📑 Fields of Interest

Not every field in your file matters for reconciliation.

Fields of Interest are the columns you want to carry forward for:

• Reports
• Debugging mismatches
• Audits

For example: invoiceId, vendorId, transactionDate.

📄 File Extensions

BoxPay supports a growing list of file formats so you can reconcile data no matter how it’s provided. Currently supported:

• CSV
• XLS / XLSX / XLSB
• PDF

This list keeps expanding, making the system future-proof.

🔁 Duplicate Record Handling

What if the record with same matching parameter shows up more than once?

BoxPay lets you define Duplicate Record Handling Strategy:

• Merge → Combine records intelligently
• Latest → Keep the most recent record
• Earliest → Keep the first record
• None -> Add a random identifier to records to manage those separately

This ensures your recon stays clean even with messy data sources.

🌍 Real-World Use Cases

BoxPay Reconciliations isn’t limited to finance or payments — it’s designed to adapt across industries. Here’s where it shines:

• Bank Settlements: Match Payment Gateway transactions against Bank credits to ensure no money is lost in transit.
• Vendor Payouts: Compare Vendor Invoices with Order Management System (OMS) records to validate correct amounts before paying suppliers.
• Customer Refunds: Reconcile Refund Requests from CRM with Bank Debits to confirm all refunds are processed.
• Treasury & Accounting: Match Internal Ledger entries with External Bank Statements for seamless month-end closing.
• Insurance & Healthcare: Reconcile Claims submitted vs. Payments received across multiple providers.

✨ Wrapping Up

BoxPay Reconciliations is designed to be generic yet powerful. By configuring:

• Recon Name
• File Types & File Sets
• Matching Parameters & Recon Values
• Fields of Interest & Duplicate Strategies

… you can reconcile any dataset from any provider with minimal effort.

At BoxPay, our goal is to remove the complexity from reconciliations so you can focus on insights, not manual matching.