Scanning analytics is a type of analytical procedure used to examine financial data and other entity information at a detailed level. Unlike other types of analytical procedures that often rely on aggregated financial information, scanning analytics search within accounts or other entity data to identify anomalous individual items.
Understanding Scanning Analytics
Scanning analytics involves a detailed review of individual transactions, balances, or data points to spot unusual patterns, unexpected entries, or specific items that warrant further investigation. Its primary goal is to pinpoint anomalies that might not be apparent when looking only at summarized data.
How Scanning Analytics Works
Instead of comparing account balances from one period to another or analyzing ratios (which are common in other analytical procedures), scanning analytics dives deeper. Examples include:
- Reviewing a list of all transactions within a particular account to identify unusually large or small amounts.
- Searching for specific keywords or patterns in transaction descriptions (e.g., identifying payments coded to unusual vendors).
- Examining journal entries for entries made by individuals who don't typically make such entries or entries made outside of normal business hours.
- Looking for duplicate payments or transactions.
This granular examination allows auditors or analysts to identify specific items that deviate from expectations or established norms, potentially indicating errors, fraud, or other issues.
Scanning vs. Other Analytical Procedures
| Feature | Scanning Analytics | Other Analytical Procedures |
|---|---|---|
| Focus Level | Individual items within accounts/data | Aggregated financial information (balances, totals) |
| Primary Goal | Identify anomalous individual items | Identify unusual trends or relationships |
| Data Used | Detailed transaction lists, individual entries, etc. | Summarized financial statements, account totals |
As highlighted by the definition, scanning analytics' strength lies in its ability to find irregularities hidden within the volume of data, which might be averaged out or obscured when only summary figures are reviewed.
Applications and Benefits
Scanning analytics is a powerful tool in various contexts, particularly in auditing, fraud detection, and financial analysis.
- Auditing: Helps auditors identify specific transactions that require detailed testing.
- Fraud Detection: Can uncover individual fraudulent transactions or entries that might be small relative to total balances but significant in nature.
- Financial Analysis: Allows analysts to understand the composition of accounts and identify specific drivers of change or unusual items impacting performance.
By focusing on the individual data points, scanning analytics provides a critical layer of scrutiny that complements procedures using aggregated data, offering a more complete view of potential risks or issues within an entity's records.
