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Journal Entry Monitoring
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☷ Journal Entry Monitoring
Journal Entry Continuous Monitoring
AI-powered detection of fraud indicators, timing anomalies, Benford's Law deviations, and segregation of duties violations in journal entries.
⚙ Configure Rules
⇧ Upload & Analyze
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JEs Analyzed
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High Severity
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Medium Severity
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Low Severity
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Value at Risk
⚙ Configure Rules
⇧ Upload & Analyze
◕ Results
↻ Run History
⚙
Rule Library — Journal Entry Monitoring
Toggle rules on/off. Based on MindBridge and big-4 JE testing methodologies.
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+ Add Custom Rule
Rule Name
Severity
High
Medium
Low
Description
Add Rule
⇧
Upload GL / Journal Entry Data
📄
Drop your GL or JE extract here
Supports CSV and Excel exports from SAP, Oracle, NetSuite, QuickBooks, and other ERP systems.
CSV
XLSX
XLS
Choose File
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Analysis Configuration
Entity / Company
Period / Fiscal Year
Re-run continuity
Context from process-owner discussions
Baseline run (optional)
No baseline (fresh analysis)
Or upload previous output CSV
No baseline selected.
0
rules enabled ·
configure rules
Data Preview (first 5 rows)
▶ Run AI Analysis
Analyzing journal entries…
Preparing data
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No analysis run yet
Upload GL/JE data and run the AI analysis to see findings here.
⇧ Upload & Run
Viewing a past run — read-only.
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JEs Analyzed
0
High
0
Medium
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Low
$0
Value at Risk
Severity Distribution
Exceptions by Category
🧠 AI Executive Summary
All Findings
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High
Medium
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⤓ Export CSV
Save this analysis as a workpaper for your engagement file.
☁ Save as Workpaper
Run History
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