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    Ouderdomsbalans Analyse

    4

    Automated Dutch accounts receivable aging analysis (ouderdomsbalans) with Python-driven bucket categorization.

    $7

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    See it in action

    You say

    Maak een ouderdomsbalans van facturen.csv met peildatum 2026-06-10 en controleer de top 3 risico's.

    Your agent does

    Analyse voltooid op peildatum 2026-06-10. Totaal openstaand: €142.500 (>90d: 31%). Top 3 Risico's:

    1. Klant Janssen: €5.445 (>90d, factuur 2025-201)
    2. BVBA De Smet: €3.200 (61-90d)
    3. Firma Pieters: €1.150 (>90d) Check 400-rekening aansluiting; adviseer bespreking waardevermindering voor Janssen.

    What you get

    Generate an aging report for period-end closing and GL reconciliationIdentify overdue customers for debt collection and dunning actionsCalculate the percentage of debt >90 days for bad debt provisioningAutomate the netting of credit notes against outstanding customer balances

    About this skill

    Automated Accounts Receivable Aging Analysis

    This skill automates the creation of an "Ouderdomsbalans" (Aging Report), a critical task for accountants and financial controllers. It processes raw invoice exports to categorize outstanding balances into aging buckets, providing a clear overview of credit risk and liquidity.

    What it does

    The skill utilizes a Python-based processing engine to transform a CSV export containing customer names, invoice numbers, due dates, and amounts. It handles partial payments, credit notes, and net balance calculations per customer.

    • Bucket Distribution: Categorizes receivables into Not Due, 1-30, 31-60, 61-90, and >90 days.
    • Deep-Dive Reporting: Generates a specific detail block for items over 90 days, facilitating immediate action on bad debt.
    • Reconciliation Flagging: Compares results against General Ledger (GL) balances to identify export discrepancies.
    • Strategic Insights: Calculates the ">90-day percentage" and identifies top-risk customers to guide provision discussions.

    Why use this skill?

    Manual aging reports in Excel are prone to formula errors and struggle with credit note netting. This skill ensures a consistent, programmatic approach that is repeatable for every period-end closing. It transitions the accountant from data entry to data analysis, focusing on which debts are truly doubtful.

    Built by Nex AI. More skills and info at nex-ai.be and slopsome.com.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Listed2 months ago
    Updated12 days ago

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