Audit Analyses

Using different account categories such as accounts payable, accounts receivable, and liquid assets, we explore useful audit analyses. We explain why these analyses are important and guide you through them step by step, making it easy for you to apply them yourself.

Supplier analysis for auditors

ACCOUNTS-PAYABLE

Use python to analayze product price trends, compare regions and flag anomalies in your acounts payable data.

Supplier analysis for auditors

Use python to analayze product price trends, compare regions and flag anomalies in your acounts payable data.

Reconcile purchase invoices

In this article, we reconcile purchase invoices with the general ledger (auditfile). Are we complete, and do the amounts match correctly?

How to Audit Accounts Payable with Data Analysis

What does the accounts payable balance represent, how does it arise, and how is it audited? This article explains the accounts payable process step by step and provides context for analyses that can offer deeper insights.

Purchase price analysis - trends, supplier comparison and price outliers

In this article, we develop a python script to analyse product prices and compare suppliers.

3-way match (AR): invoices, orders, and deliveries

Complete 3-way match analysis: tie out sales invoices, sales orders, and deliveries with Python.

Aging Analysis & Doubtful Debtors: Analysis with Python

Discover how to perform an aging analysis on outstanding accounts receivable with Python. Identify doubtful debtors and improve your audit approach with data analysis.

Benford’s Law in Audit Practice: Identifying Irregular Number Patterns

ow to use Benford’s Law to identify irregular number patterns in financial data, including a Python example and MAD test.

K-means clustering in auditing: clustering & outliers

Learn how K-means structure data. Group transactions, spot and understand when this machine-learning technique is appropriate in audit.

Inventory Aging Analysis (FIFO)

In this article, we analyze the age of inventory to identify obsolete goods. Using Python, we create an overview of slow-moving stock.

Inventory turnover analysis

Calculate product turnover using sales and turnover and average stock. Identify slow moving items and improve inventory management (incl. script)

Money–Goods movement (reconcile stock movements with general ledger)

In this article we verify whether inventory movements reconcile with the financial records using the formula: Opening Inventory + Purchases – Closing Inventory = Sales.

CAMT.053 | Explanation & Converter

In this article, we delve into CAMT files and share a Python script to convert them into Excel or CSV.

Duplicate Bank Account Check (CAMT)

In this article, we use Python and a CAMT-053 file to identify duplicate IBANs in bank transactions. A data analysis on cash and bank balances.

Analyzing Transactions to (High-Risk) Countries (CAMT and FATF List)

This analysis helps you detect payments to high-risk countries based on the FATF list, using CAMT bank data.

Split-payment analysis (detect split below approval)

In this article, we use Python and a CAMT-053 file to identify suspicious split payments. Discover patterns where transactions may be circumventing approval thresholds (incl. script).