Guide
Automating Quality of Earnings (QOE) analysis with AI
AI can prepare most of a Quality of Earnings (QOE) analysis: Vizabiliti QOE takes P&L, balance sheet, general ledger, receivables, payables and sales exports, maps accounts using industry rules, recasts the P&L, builds the EBITDA bridge and working capital, flags anomalies, and produces a cross-validated Excel report. Analysts review and sign off every adjustment.
What a QOE analysis is
A Quality of Earnings analysis reviews a company's reported earnings and adjusts for one-off and non-operating items to show sustainable profitability. It is used in acquisitions, investments and lending.
Manual QOE vs Vizabiliti QOE
| Task | Manual process | Vizabiliti QOE |
|---|---|---|
| Data intake | Spreadsheets rekeyed by hand | Uploads for 6 source file types (P&L, balance sheet, GL, AR, AP, sales) |
| Account mapping | Analyst judgement per engagement | Industry mappings, auto-mapping and a trace for every account |
| Adjustments | Built in separate workbooks | Addbacks, cash proof and revenue concentration, cross-checked |
| Anomalies | Found by sampling | AI anomaly detection and Data Insights chat |
| Report | Assembled and tied out manually | Multi-tab Excel report that ties across tabs |
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Frequently asked questions
What data does QOE need?
Exports of the profit and loss statement, balance sheet, general ledger, receivables and payables ageing, and sales by customer, in CSV or Excel.
Which industries does it cover?
Engagements are tagged by industry, from construction to SaaS, with six industry mappings that can be overridden per engagement.
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