In any accounting system, reconciliation is a critical process. It's how we ensure that different financial records align correctly - matching bank statements with invoices, payments with expenses, and so on. Today, we'd like to introduce the matchable concept implemented in Quantledger.

What is a Matchable?

At its core, a matchable is a standardized financial entity that can be paired with other entities during reconciliation. Think of matchables as financial puzzle pieces - each representing a transaction from different sources that can be connected together.

In Quantledger, matchables can be derived from:

• Bank statement lines
• Journal entries
• Supporting documents
• Supplier invoices
• Customer invoices

Multiple Matchables from a Single Source

An important aspect to understand is that a single source (documents, statement lines, and so on) can generate multiple matchables. For example, invoices typically produce two distinct matchables:

1. One based on the invoice issue date
2. Another based on the due date

This dual representation allows the system to match transactions either when an invoice is issued or when payment is expected, providing flexibility in the reconciliation process.

Another common example is statement lines where a single line has two currency amounts listed, one being the foreign amount. This results in one matchable for each currency, both connected to the same line.

Synthetic Matchables for Currency Handling

A notable feature is the creation of synthetic matchables to handle multi-currency scenarios. When a transaction isn't in our base currency (EUR), the system:

• Maintains the original currency and amount as one matchable
• Creates an additional EUR-denominated synthetic matchable using exchange rate data from the European Central Bank

This approach addresses a common reconciliation challenge - matching transactions that might be recorded in different currencies across different systems.

For example, with a $1,000 USD transaction, both a USD matchable and an EUR matchable are created. This approach provides flexibility when matching with other transactions that might be in either currency.

The Value of Matchables

Many accounting systems treat different financial records as separate entities, making reconciliation a manual process. By converting various financial entities into matchables, Quantledger creates a unified approach that offers several helpful features:

1. Currency Normalization: Matchables can be converted to a standard currency for easier comparison.
2. Flexible Matching: The system can match entities based on multiple criteria.
3. Complete Audit Trail: Each matchable maintains references to its source, providing traceability.

Practical Applications

This matchable architecture can help with:

• Identifying matching transactions across document types
• Reducing matching errors through standardization
• Maintaining clear links to original documents
• Supporting multi-currency environments

Beyond Basic Matching

While matching on dates and amounts is effective for many reconciliation scenarios, some cases present ambiguity that requires more sophisticated approaches. For these situations, Quantledger incorporates:

• AI-assisted matching: Using language models and embeddings to understand the context of transactions when numerical data alone isn't sufficient
• Pattern recognition: Identifying recurring transaction patterns that might not be evident through traditional matching methods
• Human-in-the-loop verification: Presenting suggested matches with confidence scores rather than making autonomous decisions

This balanced approach ensures that the system remains transparent rather than functioning as a black box. Users maintain visibility and control over the matching process while benefiting from advanced matching suggestions in complex cases.

Conclusion

The matchable concept offers a practical approach to accounting reconciliation by providing a consistent format for different financial transactions. By converting various document types into comparable entities, Quantledger helps connect related financial records more efficiently. This standardization can make reconciliation more straightforward while helping maintain accuracy.

In future posts, we'll share examples of how matchables work in everyday reconciliation scenarios.

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