Creating a matching rule
To create a new matching rule, call the Create matching rule endpoint:Response
Editing and deleting matching rules
After creating a matching rule, you can update it or remove it when it’s no longer needed:- Update: Use the Update matching rule endpoint to change the name, description, or criteria of an existing rule.
- Delete: Use the Delete matching rule endpoint to remove a rule from your reconciliation workflows.
How Blnk matches transactions during reconciliation
Blnk ensures accurate reconciliation by comparing external records with your ledger records based on five key attributes:| Attributes | Operators | What it does |
|---|---|---|
amount | equals, greater_than, less_than | Compares transaction amounts. |
currency | equals | Ensures both transactions use the same currency. |
date | equals, after, before | Matches transactions based on their timestamps. |
reference | equals, contains | Checks if the transaction reference matches or is partially included. |
description | equals, contains | Matches transactions based on their descriptions. |
Understanding matching operators
Each attribute is matched using specific operators, which determine how strict the comparison is:| Operators | Description |
|---|---|
equals | Both records must match exactly. |
contains | Parts of the external record match the internal record. |
greater_than | The external amount must be higher than the internal amount. |
less_than | The external amount must be lower than the internal amount. |
after | The external date must be later than the internal date. |
before | The external date must be earlier than the internal date. |
Example scenarios
Here’s how these rules work during reconciliation:Matching amounts
| External amount | Internal amount | Operator used | Match? |
|---|---|---|---|
| $100.00 | $100.00 | equals | ✅ Yes |
| $105.00 | $100.00 | greater_than | ✅ Yes |
| $95.00 | $100.00 | greater_than | ❌ No |
Matching dates
| External date | Internal date | Operator used | Match? |
|---|---|---|---|
| March 10, 2025 | March 10, 2025 | equals | ✅ Yes |
| March 12, 2025 | March 11, 2025 | after | ✅ Yes |
| March 10, 2025 | March 11, 2025 | after | ❌ No |
Why this matters
-
Flexibility: Use operators like
contains,greater_than, andbeforeto account for processing delays, fees, and partial matches. - Precision: Ensure transactions are matched accurately, reducing errors in reconciliation.
- Control: Customize your matching rules to fit your financial workflows.
Handling discrepancies with drifts
Small differences in amounts or dates—like fees or time zone shifts—can disrupt reconciliation. Theallowable_drift field sets a tolerance range for matches, used with the equals operator. Blnk supports two types:
-
Amount drift: Tolerates value differences (e.g., 0.01 = 1% drift).
A $100 internal record with 1% drift matches $99 – $101 external records.
-
Date drift: Allows for time differences (e.g., 3600 = 1 hour).
A 2:00 PM internal record with 1-hour drift matches 1:00–3:00 PM external timestamps.
When to use drifts
-
Use amount drift when:
- Your external data includes processing fees or minor exchange rate variations.
- Your system rounds transactions differently from external sources.
-
Use date drift when:
- Your transactions involve cross-time-zone processing.
- Payment settlements take hours or days to finalize.
Best practices
To ensure accurate and reliable financial reconciliation, follow these best practices when defining matching rules:- Optimize for efficiency: Reduce manual effort by implementing automated matching rules.
- Use Drifts Strategically: Apply allowable drifts to handle small discrepancies without compromising accuracy.
- Ensure accuracy: Minimize human errors with consistent and precise rule application.
- Design for scalability: Use robust rules that can handle high transaction volumes and complex financial products.
- Maintain compliance: Align matching rules with regulatory requirements for transparency.
- Regularly review & optimize: Continuously assess and refine matching rules based on reconciliation performance and error patterns.
- Audit logs: Maintain detailed logs of matching decisions to support audits and troubleshooting.