Transaction Matching

Purpose

Provides rules for linking an uploaded receipt to an existing bank transaction in transactions.csv. Uses amount, date, and merchant name as matching signals with confidence scoring.

Matching Signals

Three signals determine whether a receipt matches a transaction:

Signal	Weight	Rule
Amount	Primary	Receipt total (positive) must match transaction amount (negative) within +-1%
Date	Primary	Receipt date must be within +-1 day of transaction date
Merchant	Secondary	Normalized merchant name should match (boosts confidence but not required)

Both amount and date must match for a candidate. Merchant match increases confidence but a missing merchant match does not disqualify.

Amount Comparison

Receipts store totals as positive numbers. Transactions store expenses as negative numbers. When comparing:

1. Take the absolute value of the transaction amount
2. Compare with the receipt total
3. Allow +-1% tolerance

Formula: |receipt_total - |transaction_amount|| / receipt_total <= 0.01

Why +-1%: Small rounding differences between what the store charges and what the bank posts (e.g., currency conversion micro-adjustments, tip rounding).

Examples

Receipt Total	Transaction Amount	Difference	Match?
347.50	-347.50	0.00%	Yes
347.50	-348.00	0.14%	Yes
347.50	-344.00	1.01%	No
299.00	-299.00	0.00%	Yes

Date Window

Card transactions often post 1 business day after the purchase. Allow a +-1 day window:

• Receipt date: 2026-01-28
• Valid transaction dates: 2026-01-27, 2026-01-28, 2026-01-29

Why +-1 day: Dankort and Visa purchases at end of day may post the next morning. Some merchants batch transactions overnight.

Merchant Name Matching

Compare the receipt's normalized merchant name against the transaction's description using the same normalization rules from skills/categorization/SKILL.md:

1. Uppercase both strings
2. Check if the receipt merchant appears anywhere in the transaction description
3. Account for common abbreviations (Foetex = FOETEX, Netto = NETTO)

Merchant match is a confidence booster, not a hard requirement. Some transactions have generic descriptions that don't include the merchant name (e.g., "Dankort-koeb" without store name).

Confidence Scoring

Scenario	Confidence	Action
1 match: amount + date + merchant	1.0	Auto-link
1 match: amount + date (no merchant)	0.9	Auto-link
2-3 matches: amount + date	0.7	Present candidates to user
4+ matches: amount + date	0.5	Present candidates to user
Amount matches but date outside window	0.3	Present as weak candidate
No amount match	0.0	Unmatched

Matching Workflow

Execute these steps in order:

Step 1: Search Candidates

Read transactions.csv and filter for transactions where:

• |transaction_amount| is within +-1% of receipt total
• date is within +-1 day of receipt date
• Transaction is an expense (amount < 0)

Step 2: Score Candidates

For each candidate, calculate confidence:

1. Start with 0.8 (amount + date match)
2. Add 0.1 if merchant name matches
3. Add 0.1 if date is exact (same day, not +-1)

Cap at 1.0.

Step 3: Decide

Candidates	Best Confidence	Action
0	—	Store as unmatched
1	>= 0.8	Auto-link, set match_status: matched
1	< 0.8	Present to user for confirmation
2+	any	Present all candidates to user

Step 4: Present Candidates (if needed)

Show the user a numbered list:

Jeg fandt {n} mulige transaktioner til denne kvittering:

1. {date} — {description} — {amount} kr (match: {confidence_pct}%)
2. {date} — {description} — {amount} kr (match: {confidence_pct}%)

Hvilken transaktion hoerer kvitteringen til? (Eller "ingen" hvis ingen passer)

Step 5: Link or Store Unmatched

• User picks a candidate: Set transaction_id to the selected tx_id, match_status: matched, match_confidence to the calculated confidence
• User says "ingen": Set transaction_id to empty, match_status: unmatched, match_confidence: 0.0
• Auto-linked: Set transaction_id, match_status: matched, match_confidence from step 2

Already-Matched Transactions

Before matching, check if the candidate transaction already has a receipt linked:

1. Read receipts.csv
2. Check if any row has the candidate's tx_id as transaction_id
3. If yes, warn: "Denne transaktion ({date}, {amount} kr) har allerede en kvittering ({receipt_id}). Vil du tilfoeje endnu en?"

A transaction can have multiple receipts (e.g., split payments across stores for the same total), but this should be a deliberate user choice.

Examples

Example 1: Auto-Match (Single Clear Match)

Receipt: Foetex, 2026-01-28, 347.50 kr

Transactions search (date 2026-01-27 to 2026-01-29, amount 344.03 to 351.00):

tx-uuid-001  2026-01-28  -347.50  "Dankort-køb FØTEX ØSTERBRO"

Result: 1 candidate, confidence 1.0 (amount exact + date exact + merchant match "FOETEX") Action: Auto-link. match_status: matched, match_confidence: 1.0

Example 2: Ambiguous (Multiple Candidates)

Receipt: Netto, 2026-01-20, 189.50 kr

Transactions search:

tx-uuid-010  2026-01-20  -189.50  "Dankort-køb NETTO 1234"
tx-uuid-011  2026-01-19  -190.00  "Dankort-køb NETTO 5678"

Candidate 1: confidence 1.0 (exact amount + exact date + merchant) Candidate 2: confidence 0.8 (amount within 0.26% + date -1 day + merchant)

Action: Present both to user:

Jeg fandt 2 mulige transaktioner til denne kvittering:

1. 20. jan — Dankort-køb NETTO 1234 — 189,50 kr (match: 100%)
2. 19. jan — Dankort-køb NETTO 5678 — 190,00 kr (match: 80%)

Hvilken transaktion hører kvitteringen til? (Eller "ingen" hvis ingen passer)

Example 3: No Match

Receipt: Restaurant Cofoco, 2026-01-25, 1.250.00 kr

Transactions search (date 2026-01-24 to 2026-01-26, amount 1237.50 to 1262.50): No transactions found.

Action: Store as unmatched. match_status: unmatched, match_confidence: 0.0

Output: "Ingen matchende transaktion fundet. Kvitteringen er gemt som ikke-matchet. Du kan matche den manuelt senere."

Edge Cases

Weekend/Holiday Posting Delays

Some transactions post with a 2-3 day delay over weekends. The +-1 day window handles most cases. If a user reports a missing match, suggest they check if the transaction has posted yet.

Split Payments

If a user paid with two methods (e.g., partly MobilePay, partly Dankort), the receipt total won't match either transaction. The receipt will be stored as unmatched. The user can manually link it later.

Foreign Currency

If the receipt is in a foreign currency, the amount comparison should use the DKK amount from the bank transaction, not the foreign currency amount on the receipt. This means auto-matching is less reliable for foreign receipts — flag with lower confidence (0.5-0.7 even for good matches).

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Payslip-to-Transaction Matching

Purpose

Links uploaded payslips to salary deposit transactions in transactions.csv. Uses net_salary amount, deposit timing, and description patterns.

Matching Signals

Signal	Weight	Rule
Amount	Primary	Net salary must match transaction amount within ±1%
Date	Primary	Transaction date must be within 5 days after pay_period end
Type	Required	Transaction must be CRDT (credit/income)
Description	Secondary	Should contain "Løn", "Salary", or employer name

Date Window

Salary is typically deposited at the end of the pay period or within the first few days of the next month:

• Pay period: 2026-01 (January)
• Valid transaction dates: 2026-01-25 to 2026-02-05

Why this window: Most Danish employers pay on the last working day of the month, but some pay on a fixed date (e.g., 25th) or in the first days of the following month.

Amount Comparison

Payslips store net_salary as a positive number. Salary transactions are positive (CRDT).

Formula: |payslip_net - transaction_amount| / payslip_net <= 0.01

Why ±1%: Minor differences can occur from rounding or small adjustments not shown on the payslip.

Description Patterns

Look for these patterns in transaction descriptions:

Pattern	Example	Confidence Boost
"Løn"	"Løn januar", "LOEN FRA..."	+0.1
"Salary"	"Salary payment"	+0.1
Employer name	"Teknologi A/S", "TEKNOLOGI"	+0.15
Period reference	"Jan 2026", "202601"	+0.05

Confidence Scoring

Scenario	Confidence	Action
1 match: amount + date + description patterns	1.0	Auto-link
1 match: amount + date (no description match)	0.85	Auto-link
2-3 matches: amount + date	0.7	Present candidates to user
Amount matches but date outside window	0.4	Present as weak candidate
No amount match	0.0	Unmatched

Matching Workflow

Step 1: Determine Search Window

Calculate the expected transaction date range:

• Start: 5 days before pay_period end (e.g., Jan 25 for January payslip)
• End: 5 days after pay_period end (e.g., Feb 5 for January payslip)

Step 2: Search Candidates

Read transactions.csv and filter for transactions where:

• amount is positive (income)
• |amount - net_salary| / net_salary <= 0.01
• date is within the calculated window

Step 3: Score Candidates

For each candidate, calculate confidence:

1. Start with 0.8 (amount + date match)
2. Add 0.1 if "Løn" or "Salary" in description
3. Add 0.05 if employer name appears in description
4. Add 0.05 if date is last working day of month

Cap at 1.0.

Step 4: Decide

Candidates	Best Confidence	Action
0	—	Store as unmatched
1	>= 0.8	Auto-link
1	< 0.8	Present to user for confirmation
2+	any	Present all candidates to user

Already-Matched Transactions

Before matching, check if the candidate transaction already has a payslip linked:

1. Read payslips.csv
2. Check if any row has the candidate's tx_id as transaction_id
3. If yes, warn: "Denne transaktion ({date}, {amount} kr) har allerede en lønseddel ({payslip_id}). Vil du tilføje endnu en?"

A transaction should typically have only one payslip, but users may have corrections or supplementary payments.

Examples

Example 1: Clear Salary Match

Payslip: Teknologi A/S, January 2026, net_salary: 25,245.35 kr

Transactions search (Jan 25 - Feb 5, amount 24,993 - 25,498):

tx-uuid-045  2026-01-31  25245.35  "Løn Teknologi A/S januar"

Result: 1 candidate, confidence 1.0 (amount exact + date in window + "Løn" + employer name) Action: Auto-link

Example 2: Multiple Salary Candidates

Payslip: Startup ApS, January 2026, net_salary: 28,500.00 kr

Transactions search:

tx-uuid-050  2026-01-31  28500.00  "LOEN"
tx-uuid-051  2026-02-01  28500.00  "Overførsel"

Candidate 1: confidence 0.9 (amount exact + last day of month + "LOEN") Candidate 2: confidence 0.8 (amount exact + date in window, no description match)

Action: Present both to user

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Related Skills

• See skills/data-schemas/SKILL.md for the receipts.csv, payslips.csv, and complete data file structure
• See skills/document-parsing/SKILL.md for how receipt data is extracted
• See skills/payslip-parsing/SKILL.md for how payslip data is extracted
• See skills/categorization/SKILL.md for merchant name normalization rules