Rapprochement Bancaire

VérifiéSûr

Automatise le rapprochement bancaire en faisant correspondre les transactions comptables et bancaires, en détectant les écarts et en suivant les éléments en suspens. Utile pour la clôture mensuelle, la vérification des soldes et la résolution des transactions non appariées sur plusieurs comptes et devises.

Spar Skills Guide Bot
Data & IAIntermédiaire
8002/06/2026
Claude CodeCursorWindsurfCopilotCodex
#bank-reconciliation#transaction-matching#discrepancy-detection#fuzzy-matching#balance-verification

Recommandé pour

Notre avis

Automatise le rapprochement bancaire en faisant correspondre les transactions comptables et bancaires, en détectant les écarts et en générant des rapports.

Points forts

  • Importation de transactions via CSV ou Plaid
  • Correspondance exacte et floue avec tolérance de dates et montants
  • Détection des écarts et suivi des éléments en suspens
  • Génération de rapports de rapprochement structurés

Limites

  • Nécessite une configuration initiale des comptes et des règles
  • La correspondance floue peut nécessiter une validation manuelle
  • Ne gère pas les transactions multi-devises complexes
Quand l'utiliser

À utiliser pour le rapprochement mensuel des comptes bancaires ou en cas de détection d'écarts de solde.

Quand l'éviter

Éviter de l'utiliser pour des transactions en temps réel ou lorsque les données bancaires ne sont pas fiables.

Analyse de sécurité

Sûr
Score qualité88/100

The skill is a procedural guide for bank reconciliation. It instructs querying a database and generating reports, with no execution of destructive commands. It explicitly requires manual approval for adjustments and logging of actions, posing no security risk.

Aucun point d'attention détecté

Exemples

Monthly bank reconciliation
Reconcile bank account 1234 for January 2026 using the imported bank CSV file. Generate a report and flag any discrepancies.
Investigate unmatched transactions
Show me all unmatched transactions from the January reconciliation for account 1234. Identify potential fuzzy matches.
Balance verification
Verify the book balance for account 1234 equals the cleared bank balance plus outstanding items as of January 31, 2026.

name: bank-reconciliation description: "Match bank transactions to book transactions, detect discrepancies, and resolve mismatches. Use when reconciling bank accounts, investigating unmatched transactions, or generating reconciliation reports. Handles multiple accounts and currencies."

Bank Reconciliation Skill

Purpose

Automates the bank reconciliation process by matching book transactions to bank statement transactions, detecting discrepancies, and facilitating resolution.

Triggers

  • End of month reconciliation scheduled
  • User initiates manual reconciliation
  • Discrepancy detected in account balance
  • Bank feed imported via Plaid

Capabilities

  1. Transaction Import - Import bank transactions via Plaid or CSV
  2. Transaction Matching - Match book to bank transactions
  3. Discrepancy Detection - Identify unmatched transactions
  4. Fuzzy Matching - Match similar amounts and dates
  5. Outstanding Items - Track checks and deposits in transit
  6. Balance Verification - Verify book balance = cleared bank balance + outstanding items

Instructions

Step 1: Import Bank Transactions

Options:

  1. Plaid Integration - Fetch via data-sync skill
  2. CSV Upload - Parse CSV file with columns: date, description, amount
  3. Manual Entry - User inputs transactions

Step 2: Load Book Transactions

Query database for unreconciled transactions in date range:

SELECT * FROM transactions 
WHERE account_id = $1 
AND date BETWEEN $2 AND $3 
AND reconciled = FALSE

Step 3: Exact Matching

Match transactions where:

  • Date matches exactly
  • Amount matches exactly (cents)
  • Payee name matches (after normalization)

Mark as reconciled = TRUE when matched.

Step 4: Fuzzy Matching

For unmatched transactions, try fuzzy match:

  • Date proximity - Within ±3 days
  • Amount match - Exact amount
  • Payee similarity - Levenshtein distance < 3 or substring match

Present fuzzy matches for manual review.

Step 5: Discrepancy Detection

Identify discrepancies:

  • Missing from Bank - In books but not in bank statement (check in transit?)
  • Missing from Books - In bank but not in books (unrecorded transaction?)
  • Amount Mismatch - Same transaction, different amounts (data entry error?)
  • Date Mismatch - Same transaction, different dates (timing difference?)

Step 6: Outstanding Items

Track outstanding items:

  • Checks Written - In books, not yet cleared bank
  • Deposits Made - In books, not yet posted by bank

Calculate outstanding balance:

Book Balance - Outstanding Checks + Outstanding Deposits = Bank Balance

Step 7: Generate Report

Create reconciliation report:

{
  "account_id": "uuid",
  "period_start": "2026-01-01",
  "period_end": "2026-01-31",
  "book_balance": 5000000,  // cents
  "bank_balance": 4950000,  // cents
  "matched_count": 45,
  "unmatched_book_count": 2,
  "unmatched_bank_count": 1,
  "outstanding_checks": [
    {"id": "...", "amount": -25000, "payee": "..."}
  ],
  "outstanding_deposits": [
    {"id": "...", "amount": 75000}
  ],
  "discrepancies": [
    {
      "type": "missing_from_bank",
      "transaction_id": "...",
      "description": "...",
      "amount": -5000
    }
  ],
  "status": "balanced",  // or "discrepancy"
  "requires_investigation": false
}

Decision Logic

Auto-Reconcile

  • Exact match (date, amount, payee)
  • Previously reconciled (if re-running)

Manual Review Required

  • Fuzzy match (present options to user)
  • Significant discrepancy (> $100)
  • Unusual pattern (e.g., duplicate amounts)

Escalate

  • Unresolved after 3 reconciliation attempts
  • Balance off by > $1000
  • Fraud indicators detected

Integration Points

  • data-sync (via Integration Lead) - For Plaid import
  • transaction-matcher (Reconciliation worker) - For matching logic
  • discrepancy-investigator (Reconciliation worker) - For investigation
  • audit-trail - Log all reconciliation actions

Models

  • Matching: Deterministic algorithm (no LLM)
  • Payee Normalization: Claude Sonnet 4 or Gemini Flash
  • Discrepancy Investigation: Claude Sonnet 4

Security

  • Never modify historical transactions automatically
  • Require manual approval for adjustments
  • Log all reconciliation actions to audit_log
  • Preserve original bank data

Invoke this skill at month-end or when investigating account discrepancies.

Skills similaires