Match rules

Match rules are where you set your reconciliation policy — how strict or forgiving Matcher should be when deciding two transactions are the same. Tight rules mean more manual review but fewer false matches; looser rules automate more but need careful oversight. You can enforce exact matches, allow controlled variance, tolerate timing differences, or compare free-text references by similarity.

How rules work

When a matching run starts, Matcher evaluates rules in priority order.

Rules are evaluated from the lowest priority number to the highest.
The first rule that produces a match determines the outcome.
If no rule matches, the transaction becomes an exception.

This approach ensures deterministic matching while allowing progressively looser rules as fallbacks.

Rule types

Exact

Requires a strict match on configured fields.

Best for: Deterministic matches where values should align 1:1.

Tolerance

Allows controlled variance in amount matching.

Best for: Known variance patterns such as fees, rounding, or FX differences.

Date lag

Allows date differences between transactions.

Best for: Posting delays between systems.

Fuzzy

Replaces exact reference equality with normalized string-similarity scoring, while keeping the financial gate (amount, currency, date) exact. FUZZY always proposes a match for review and never auto-confirms.

Best for: Free-text memos or truncated references where the reference varies but the amount, currency, and date still align.

Creating match rules

Exact rule

cURL

curl -X POST "https://api.matcher.example.com/v1/contexts/{contextId}/rules" \
 -H "Authorization: Bearer $TOKEN" \
 -H "Content-Type: application/json" \
 -d '{
   "type": "EXACT",
   "priority": 1,
   "config": {
     "matchAmount": true,
     "matchCurrency": true,
     "matchDate": true,
     "matchReference": true,
     "datePrecision": "DAY",
     "caseInsensitive": true,
     "referenceMustSet": false,
     "matchBaseAmount": false,
     "matchBaseCurrency": false,
     "matchScore": 100,
     "matchBaseScore": 90
   }
 }'

Config reference

Boolean

default:"true"

Require exact amount match

Boolean

default:"true"

Require exact currency match

Boolean

default:"true"

Require exact date match

Boolean

default:"true"

Require exact reference match

String

default:"DAY"

Date comparison precision: DAY or TIMESTAMP

Boolean

default:"true"

Case-insensitive reference comparison

Boolean

default:"false"

Require reference to be present on both sides

Boolean

default:"false"

Match on base (converted) amount instead of original

Boolean

default:"false"

Match on base currency instead of original

Integer

default:"100"

Accepted and validated, but reserved/inert — does not change the calculated confidence score (see note below)

Integer

default:"90"

Accepted and validated, but reserved/inert — does not change the calculated confidence score (see note below)

matchScore and matchBaseScore are currently inert. They are accepted and validated in the rule config, but the scoring engine ignores them: confidence is always computed from the fixed internal component weights (amount 40, currency 30, date 20, reference 10). These fields are reserved for future use and setting them does not alter the confidence score or auto-confirm behavior. See Confidence scoring.

The response echoes the persisted rule with its assigned id and timestamps.

API Reference: Create match rule

Tolerance rule

cURL

curl -X POST "https://api.matcher.example.com/v1/contexts/{contextId}/rules" \
 -H "Authorization: Bearer $TOKEN" \
 -H "Content-Type: application/json" \
 -d '{
   "type": "TOLERANCE",
   "priority": 2,
   "config": {
     "percentTolerance": 0.005,
     "absTolerance": 0.50,
     "dateWindowDays": 3,
     "roundingScale": 2,
     "roundingMode": "HALF_UP",
     "percentageBase": "MAX",
     "matchCurrency": true,
     "matchReference": true,
     "caseInsensitive": true,
     "referenceMustSet": false,
     "matchBaseAmount": false,
     "matchBaseCurrency": false,
     "matchScore": 85,
     "matchBaseScore": 80
   }
 }'

Config reference

Decimal

default:"0.005"

Maximum percentage variance allowed (0.005 = 0.5%)

Decimal

default:"0.50"

Maximum absolute amount variance allowed

Integer

Number of days allowed between transaction dates

Integer

Decimal places for rounding

String

Rounding strategy: HALF_UP, BANKERS, FLOOR, CEIL, or TRUNCATE

String

Base for percentage calculation: MAX, MIN, AVERAGE, LEFT, or RIGHT

Boolean

default:"true"

Require currency match

Boolean

default:"true"

Require reference match

Boolean

default:"true"

Case-insensitive reference comparison

Boolean

default:"false"

Require reference to be present on both sides

Boolean

default:"false"

Match on base (converted) amount

Boolean

default:"false"

Match on base currency

Integer

default:"85"

Accepted and validated, but reserved/inert — does not change the calculated confidence score

Integer

default:"80"

Accepted and validated, but reserved/inert — does not change the calculated confidence score

Example:

Transaction A: $1,000.00
Transaction B: $1,005.00
Variance: 0.5% → Matches (within 0.5% tolerance and $0.50 absolute tolerance)

Fuzzy rule

cURL

curl -X POST "https://api.matcher.example.com/v1/contexts/{contextId}/rules" \
 -H "Authorization: Bearer $TOKEN" \
 -H "Content-Type: application/json" \
 -d '{
   "type": "FUZZY",
   "priority": 4,
   "config": {
     "minSimilarity": 0.85,
     "matchAmount": true,
     "matchCurrency": true,
     "matchDate": true,
     "datePrecision": "DAY",
     "referenceMustSet": true,
     "matchScore": 70
   }
 }'

Config reference

Decimal

default:"0.80"

Minimum normalized reference similarity (0–1) required to gate as a match

Boolean

default:"true"

Require exact amount match

Boolean

default:"true"

Require exact currency match

Boolean

default:"true"

Require exact date match

String

default:"DAY"

Date comparison precision: DAY or TIMESTAMP

Boolean

default:"true"

Require a non-empty reference on both sides

Integer

default:"70"

Nominal score ceiling (the graded similarity scorer drives the actual confidence)

FUZZY relaxes only the reference comparison (equality becomes similarity); the amount, currency, and date gate exactly as in an EXACT rule. Because it proposes rather than auto-confirms, its matches always land below the auto-confirm threshold for human review.

Date lag rule

cURL

curl -X POST "https://api.matcher.example.com/v1/contexts/{contextId}/rules" \
 -H "Authorization: Bearer $TOKEN" \
 -H "Content-Type: application/json" \
 -d '{
   "type": "DATE_LAG",
   "priority": 3,
   "config": {
     "maxDays": 3,
     "minDays": 0,
     "inclusive": true,
     "direction": "ABS",
     "feeTolerance": 0,
     "matchScore": 80,
     "matchCurrency": true
   }
 }'

Config reference

Integer

Maximum number of days difference allowed

Integer

default:"0"

Minimum number of days difference required

Boolean

default:"true"

Whether the boundary days are inclusive

String

default:"ABS"

How to measure the lag: ABS (absolute), LEFT_BEFORE_RIGHT, or RIGHT_BEFORE_LEFT

Decimal

default:"0"

Allowed amount difference to account for fees

Integer

default:"80"

Accepted and validated, but reserved/inert — does not change the calculated confidence score. Note that DATE_LAG rules always score the reference component as 0, capping the maximum score at 90

Boolean

default:"true"

Require currency match

Allocation settings (all rule types)

All rule types accept additional allocation settings for split and aggregate matching:

Field	Type	Description
`allowPartial`	Boolean	Allow partial allocation of transaction amounts
`allocationDirection`	String	Allocation order: `LEFT_TO_RIGHT` or `RIGHT_TO_LEFT`
`allocationToleranceMode`	String	How tolerance is measured: `ABS` (absolute) or `PERCENT`
`allocationToleranceValue`	Decimal	Tolerance threshold for allocation
`allocationUseBaseAmount`	Boolean	Use base (converted) amount for allocation

Rule priority

Rules are evaluated by priority. Lower numbers run first.

Priority strategy

Priority	Rule type	Use case
1–10	EXACT	Deterministic matches
11–50	TOLERANCE	Small, expected variance
51–100	DATE_LAG	Date differences between systems

Reorder rules

You can reorder rules by providing the rule IDs in the desired order:

cURL

curl -X POST "https://api.matcher.example.com/v1/contexts/{contextId}/rules/reorder" \
 -H "Authorization: Bearer $TOKEN" \
 -H "Content-Type: application/json" \
 -d '{
   "ruleIds": [
     "550e8400-e29b-41d4-a716-446655440001",
     "550e8400-e29b-41d4-a716-446655440002",
     "550e8400-e29b-41d4-a716-446655440000"
   ]
 }'

API Reference: Reorder match rules

Testing rules

Test rules in dry-run mode before committing matches.

cURL

curl -X POST "https://api.matcher.example.com/v1/matching/contexts/{contextId}/run" \
 -H "Authorization: Bearer $TOKEN" \
 -H "Content-Type: application/json" \
 -d '{
   "mode": "DRY_RUN"
 }'

Dry run mode evaluates all rules and shows potential matches without persisting results.

Managing rules

List rules

cURL

curl -X GET "https://api.matcher.example.com/v1/contexts/{contextId}/rules" \
 -H "Authorization: Bearer $TOKEN"

Response

The list endpoint returns a summary view of rules. To see the full configuration details for a specific rule, use the individual rule endpoint or the create response which includes the complete config object.

{
  "items": [
    {
      "id": "019c96a0-2b20-7123-9a1b-2c3d4e5f6a7b",
      "contextId": "019c96a0-2a10-7dfe-b5c1-8a1b2c3d4e5f",
      "type": "EXACT",
      "priority": 1,
      "config": {
        "matchAmount": true,
        "matchCurrency": true,
        "matchDate": true,
        "matchReference": true,
        "datePrecision": "DAY",
        "matchScore": 100,
        "matchBaseScore": 90
      },
      "createdAt": "2026-02-02T16:40:00Z",
      "updatedAt": "2026-02-02T16:40:00Z"
    }
  ],
  "limit": 20,
  "hasMore": false
}

API Reference: List match rules

Update a rule

cURL

curl -X PATCH "https://api.matcher.example.com/v1/contexts/{contextId}/rules/{ruleId}" \
 -H "Authorization: Bearer $TOKEN" \
 -H "Content-Type: application/json" \
 -d '{
   "priority": 5,
   "type": "TOLERANCE",
   "config": {
     "percentTolerance": 0.02,
     "absTolerance": 10.0
   }
 }'

API Reference: Update match rule

Delete a rule

cURL

curl -X DELETE "https://api.matcher.example.com/v1/contexts/{contextId}/rules/{ruleId}" \
 -H "Authorization: Bearer $TOKEN"

API Reference: Delete match rule

Best practices

Start strict, then loosen

Lead with exact rules. Add tolerance rules only for the variance you can justify and explain.

Leave room in priorities

Use gaps (1, 10, 20, 50) so you can insert rules without renumbering your entire set.

Dry-run every change

Treat rule updates as production changes. Validate match rates and exception volume before committing.

Write descriptions that explain intent

A rule should document the variance it covers and the risk it introduces.

Review rule output over time

If a rule never matches, it may be unnecessary. If it matches too often, it may be too broad.

Keep loose rules at low priority

High tolerance increases false positives. Use it as a fallback and review results carefully.

Next steps

Exception routing

Configure classification, assignment, and escalation for unmatched transactions.

Confidence scoring

Understand how scores are calculated and how thresholds impact automation.

Overview

Guides

Matcher UI

MCP Server

Operations

How rules work

Rule types

Exact

Tolerance

Date lag

Fuzzy

Creating match rules

Exact rule

Config reference

Tolerance rule

Config reference

Fuzzy rule

Config reference

Date lag rule

Config reference

Allocation settings (all rule types)

Rule priority

Priority strategy

Reorder rules

Testing rules

Managing rules

List rules

Response

Update a rule

Delete a rule

Best practices

Next steps

Exception routing

Confidence scoring

​How rules work

​Rule types

​Exact

​Tolerance

​Date lag

​Fuzzy

​Creating match rules

​Exact rule

​Config reference

​Tolerance rule

​Config reference

​Fuzzy rule

​Config reference

​Date lag rule

​Config reference

​Allocation settings (all rule types)

​Rule priority

​Priority strategy

​Reorder rules

​Testing rules

​Managing rules

​List rules

​Response

​Update a rule

​Delete a rule

​Best practices

​Next steps

Exception routing

Confidence scoring

How rules work

Rule types

Exact

Tolerance

Date lag

Fuzzy

Creating match rules

Exact rule

Config reference

Tolerance rule

Config reference

Fuzzy rule

Config reference

Date lag rule

Config reference

Allocation settings (all rule types)

Rule priority

Priority strategy

Reorder rules

Testing rules

Managing rules

List rules

Response

Update a rule

Delete a rule

Best practices

Next steps