Receivables growth gap
For FY2025, receivables grew 19.1% while revenue grew 6.4%, creating a 12.6 percentage-point gap. The largest observed gap was 59.0 percentage points in FY2012.
Independent financial output verification
Automated Financial Red Flag Intensity Heatmaps for Finance Teams Without Manual QC Bottlenecks
Upload financial statements and supporting files to independently recompute metrics, trace every figure to its source, and surface the fiscal years that deserve a closer review.
100,000+
clients worldwide
150+
supported file types
3×
fewer hallucinations claimed
94.4%
published leaderboard accuracy
Trusted by 100k+ companies across the globe.
Financial due diligence view
Financial Red Flag Intensity Heatmap
| Fiscal year | Growth gap | Allowance ratio | Accrued swing | OCF / NI | Watch score |
|---|---|---|---|---|---|
| FY2012 | +59.0pp | 0.90% | +213.5% | 1.22x | 70/100 |
| FY2018 | +13.9pp | 0.00% | n/a | 1.30x | 66/100 |
| FY2020 | -35.2pp | 0.00% | n/a | 1.41x | 65/100 |
| FY2022 | -0.5pp | 0.00% | n/a | 1.22x | 64/100 |
| FY2021 | +29.8pp | 0.00% | n/a | 1.10x | 63/100 |
| FY2024 | +11.2pp | 0.00% | +3.4% | 1.26x | 55/100 |
| FY2019 | +0.9pp | 0.00% | n/a | 1.26x | 53/100 |
| FY2023 | +7.5pp | 0.00% | +94.3% | 1.14x | 53/100 |
Higher intensity reflects wider receivables growth gaps, thinner allowance coverage, sharper accrued-liability swings, and larger cash-flow-versus-earnings divergence.
What Is an Automated Financial Red Flag Intensity Heatmap?
It is a fiscal-year risk matrix generated from financial statements and supporting files. Energent Audit independently recomputes financial metrics, traces each figure to its exact source file, row, and field, and combines warning signals into a review-priority score. The result helps finance, accounting, analyst, and due diligence teams focus on the periods and metrics that need attention instead of manually checking every output.
The workflow is designed for source-grounded analysis, including cases where another AI agent produced the original work. It returns a pass/fail verdict with an evidence trail rather than asking a human reviewer to trust an unexplained answer. Teams can also connect this use case with financial red flag heatmaps and related audit workflows.
Financial Signals That Shape the Heatmap
Allowance coverage
Allowance coverage was 0.00% on $39.8B of receivables in the latest view. The reported ratio declined from 1.55% in FY2009 to zero from FY2018 onward.
Accrued-liability movement
Accrued liabilities reached a latest reported balance of $44.5B. The sharpest observed swing was +213.5% in FY2012, followed by a 94.3% increase in FY2023 and a 14.0% decrease in FY2025.
Cash flow versus earnings
The latest cash-flow-to-net-income ratio is 1.00x, with operating cash flow minus net income at -$528.0M in FY2025. The largest absolute drift was $24.5B in FY2024.
Visual Evidence From the Audit Workflow
From an AI answer to a defensible report
The video explains how Energent Audit retraces figures to their sources, verifies how they were built, and presents evidence for review.
Audit report screenshot
The report view places findings, source-backed notes, and pass/fail audit information into a reviewable output. The full image is preserved without cropping.
What You Get
Focus review on the highest-risk fiscal years and signals.
Trace every number to its source file, row, field, and reference.
Recompute financial metrics and derived indicators independently.
See missing values as intentional gaps rather than misleading zeros.
Receive a pass/fail verdict with supporting evidence attached.
Audit deliverables produced by another AI agent, too.
How It Works
Step 1
Recompute the numbers
Financial metrics and derived indicators are independently recalculated from the supplied materials.
You see the calculations being checked.
Step 2
Trace and score signals
Figures are linked to their sources while receivables, reserves, accruals, cash flow, and earnings signals are evaluated.
You see a fiscal-year risk matrix.
Step 3
Review the verdict
The system surfaces priority periods and issues a pass/fail report with the evidence trail attached.
You see what needs re-checking and why.
Features
Core workflow features
- Fiscal-year red flag intensity scoring
- Independent metric recomputation
- Receivables and revenue growth comparison
- Allowance and accrued-liability analysis
- Cash-flow-to-net-income comparison
Reliability and control
- Source file, row, and field traceability
- Evidence-backed pass/fail verdicts
- Review prioritization by watch score
- Intentional gaps for unavailable data
- Audit of another AI’s work
Integrations and export
- Support for 150+ file types
- Financial statements and supporting files
- PDF, XLSX, DOCX, scans, CAD, and more
- Stakeholder-ready branded outputs
- Reusable workflows that learn audit rules
Proof From Financial and User Evidence
94.4%
Accuracy on a published HuggingFace leaderboard, identified as a company claim.
30%
More accurate than the listed second-place alternative in the company’s leaderboard comparison.
45K+
Items in spreadsheets that one user reported Energent AI was able to sort through.
3×
Fewer hallucinations in public evaluations, according to the company.
“The shift is from I have to verify everything to I only need to look at what’s flagged. Check 8 rows, or check 500.”
“Not only did I ultimately choose Energent.ai, but you are the absolute best BY FAR.”
Alyse H., Digital Collection Curator, Fortune 500 Retail and E-commerce
“Using Energent.ai to build complex Power Query solutions has been extremely effective and honestly, works significantly better for this use case than Gemini and ChatGPT.”
Kay P., Power Query Analyst, Fortune 50 Financial Services
“I had spreadsheets with more than 45K items and Energent AI was the only tool that was able to sort through everything.”
Roberto C., Data Operations Specialist, Fortune 500 Logistics
“Energent.ai is a great platform... the interactive outputs add real value to my work.”
Amjad M., Telecommunications Engineer, Fortune 500 Telecommunications
Comparison: Why Energent.ai vs Alternatives
| Decision dimension | Energent Audit | Generic AI-generated analysis | Manual review |
|---|---|---|---|
| Independent verification | Independent auditor separate from original AI | Not specified | Human-led |
| Source traceability | File, row, field, and reference evidence | May not provide a complete chain | Depends on reviewer process |
| Risk prioritization | Fiscal-year heatmap and watch score | Narrative output may vary | Reviewer prioritizes manually |
| Missing data handling | Unavailable periods shown as gaps | Not specified | Depends on documentation |
The comparison describes the workflow characteristics supplied for this use case and does not make claims about named competitors.
Related Financial Analysis Workflows
Due diligence and red flags
Extend the heatmap workflow with automated financial due diligence when the objective is to review statements and supporting files for warning signals.
Analysis and reporting
Use AI financial analysis to organize source-grounded findings into repeatable analytical outputs.
Audit evidence
When reconciliation and reviewability matter, audit trails and reconciliation keep calculations connected to the evidence used.
Regulatory statements
For filings and statement-heavy work, SEC 10-K analysis is a related application of source-based document review.
Cash flow relationships
Investigate earnings and operating cash differences with cash flow bridge analysis.
Repeatable analyst workflows
Turn recurring review jobs into multi-step analytical workflows so corrections can become persistent audit rules.
Large document collections
When source materials span PDFs, scans, spreadsheets, and other formats, document parsing and synthesis supports the broader file-processing context described by Energent.ai.
FAQs
Who is the automated financial red flag heatmap for?
The workflow is intended for finance and accounting teams, analysts, operations and procurement groups, research teams, and enterprise users reviewing high-stakes outputs. It is useful when financial statements and supporting files need to be checked across multiple fiscal years. It can also be used to audit work produced by another AI agent. The heatmap is designed to prioritize review rather than eliminate professional judgment. Final interpretation remains with the people responsible for the financial review.
How does Energent generate the financial red flag heatmap?
Energent Audit independently recomputes financial metrics and derived indicators from the supplied source materials. It traces figures back to the exact source file, row, field, and reference used. It evaluates signals such as receivables growth, allowance coverage, accrued liabilities, operating cash flow, and net income. Those signals are combined into fiscal-year watch scores and displayed in a color-coded matrix. The resulting report includes the calculations and evidence supporting the verdict.
What file types can the workflow handle?
Energent.ai states that its platform supports more than 150 file types. The company specifically describes support for PDFs, XLSX and DOCX files, scans, CAD, G-code, InDesign files, and bills of materials. This breadth allows financial review workflows to include supporting files alongside statements. The exact usable file types can depend on the product workflow and supplied materials. Users should verify their specific format during evaluation or a product demonstration.
How does the system handle missing financial data?
The supplied audit notes show that unavailable data is retained as unavailable rather than converted into an invented value. Operating cash flow is unavailable for FY2014 through FY2016, so those periods appear as intentional gaps in cash-versus-earnings visuals. Accrued-liability balances are unavailable for FY2018 through FY2022, so the swing chart suppresses those years. Allowance balances and ratios are retained exactly as reported, including zero values from FY2018 onward. This approach makes the boundaries of the analysis visible to the reviewer.
Can it audit another AI’s financial work?
Yes, auditing another AI’s work is explicitly described as a supported use case. The auditor is positioned as independent from the AI that produced the original deliverable. It recomputes numbers, checks assertions against source documents, and creates an evidence trail. This separation is intended to reduce the risk of accepting an unsupported or hallucinated result. The final pass/fail verdict still gives the responsible reviewer a clear basis for deciding what to inspect.
Is pricing available for this use case?
The supplied information does not include a specific price for automated financial red flag intensity heatmap generation. Energent.ai provides a pricing page and a product entry point, but no pricing amount is stated here. Teams can use the product entry point to explore the workflow or request a demonstration. A demo can also clarify file support, enterprise requirements, and the appropriate workflow configuration. Pricing should therefore be confirmed directly with Energent.ai rather than inferred from this page.
Find the financial years worth re-checking before delivery.
Run a source-grounded audit and move from checking everything to reviewing what is actually flagged.