R004 — Formula Inconsistency
Executive Summary
Key Takeaways
- ✓ R004 flags a formula cell whose logic differs from the dominant formula pattern the rest of its row otherwise follows — a different formula, not a typed constant.
- ✓ It is critical severity, weighted at 15.0 (tied with R001 for the highest weight in the engine), and one of five critical-override rules — a single triggered finding caps the model's letter grade below A or B.
- ✓ R004 deliberately excludes hardcoded cells from its comparison sample, so R001 and R004 never both flag the same cell for two different reasons.
- ✓ Unlike R001, a triggered R004 finding does not automatically mean an error — a deliberately different formula for a genuine exception is a legitimate outcome the finding asks a reviewer to confirm.
Purpose¶
R004 detects a formula cell whose calculation logic differs from the dominant formula pattern the rest of its row otherwise follows. It is the general case of R001: where R001 catches a typed constant overriding a row's pattern, R004 catches a different formula breaking it — an extra term, a different function, or a shifted reference relative to the row's established pattern.
Detection Logic¶
R004 examines each row of a worksheet as a group, considering only cells that contain a formula (cells containing a typed numeric value instead of a formula are deliberately excluded from this rule's sample, so that R001 and R004 never both flag the same cell for two different reasons). If a row's interior formula cells (excluding the first and last cell in the row, for the same edge-of-row reasons as R001) establish a clear, dominant formula pattern, any interior formula cell whose own formula does not match that pattern is flagged. As with R001, a row that does not establish a clear dominant pattern in the first place is not evaluated by this rule at all.
This is a conceptual description of what the rule looks for; the specific thresholds and sample-size requirements behind "a clear, dominant formula pattern" are internal to the engine and not disclosed here.
Why It Matters¶
A formula that silently diverges from its row's established pattern is one of the least visible ways a model can calculate incorrectly, because the cell still displays what looks like an ordinary calculated value — there is no typed constant and no visible error, only a formula that does something subtly different from its neighbours. If the deviation is unintentional, it represents an undetected logic error that will recalculate the same wrong way every time the model is refreshed. This is why R004 carries the same weight as R001 (15.0, the highest in the engine) and is one of five rules capable of capping a model's overall letter grade under the SM-2.0 Scoring Methodology, regardless of how high the model's numeric score otherwise is.
Evidence Produced¶
A triggered R004 finding's evidence identifies the specific sheet and cell address of the deviating formula, the cell's actual formula text, and a description stating the row's dominant pattern, how many cells follow it, and how this cell's formula differs — so the finding is traceable directly to the specific divergence that caused it to be flagged. See the Finding Data Model & Confidence page for the full evidence and provenance model this finding is built on.
Severity¶
Critical. Weight 15.0 — tied with R001 for the highest weight of any rule in the FMAE engine. R004 is one of five critical-override rules under SM-2.0 (alongside R001, R002, R006, and R023): if it triggers even once, the model's overall letter grade is capped below A or B regardless of the numeric score the weighted formula produces.
Example¶
Trigger. An operating cost row runs formula cells across five periods, four of which read =B5*1.03
(prior period times a 3% escalation factor), shifted appropriately by column. The fifth cell instead reads
=B5*1.03+15000 — the same escalation logic, but with an additional fixed amount added. R004 flags the
fifth cell: it is still a formula, but its structure diverges from the row's otherwise-consistent pattern.
Non-trigger. The same row, but every interior cell correctly reads a shifted version of =B5*1.03. No
cell's formula diverges from the row's pattern, so R004 does not fire.
Recommended Remediation¶
Because a R004 finding may reflect a legitimate, intentional exception rather than an error, remediation begins with confirming whether the deviation was deliberate. If the deviation was unintentional, the formula is corrected to match the row's dominant pattern. If it was intentional (a genuine one-off adjustment), the deviation should be documented — for example, with a cell comment explaining the exception — so a subsequent reviewer does not need to re-investigate the same question.
Related Rules¶
R004 shares the Structural taxonomy category with R001, R002, and R006, each published in this same initial phase of the Rule Reference; the remaining Structural-category rules follow in later phases and are indexed on the Rule Reference page as they are published. R001 and R004 are, specifically, a general/specific pair sharing the same row-pattern detection mechanism.
Related Articles¶
- Formula Consistency in Financial Models — the Knowledge Centre's buyer-facing technical guide to formula consistency across rows and periods.
Version History¶
No version-specific changes to R004's severity, weight, or category are recorded as of engine version 2.1.0. This section will be updated in the same edit as any future change to the rule's declared attributes.
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Frequently Asked Questions
What does FMAE rule R004 check for?
A formula cell whose calculation logic differs from the dominant pattern the rest of its row otherwise follows — for example, an extra term, a different function, or a shifted reference compared to the row's other cells.
How is R004 different from R001?
Both rules compare a row's interior cells against the row's own dominant formula pattern. R001 flags a cell that has been overridden by a typed numeric value. R004 flags a cell that still contains a formula, but a formula that differs from the row's pattern. The two rules deliberately exclude each other's target cells so the same cell is never flagged by both.
Is a R004 finding always an error?
Not necessarily. A row's cells might legitimately need different formulas for a specific, intentional exception (a one-off adjustment period, a different calculation for a stub period). R004's finding asks a reviewer to confirm whether the deviation is intentional, rather than asserting it is necessarily wrong.
Why is R004 critical severity if it might not be an error?
Because when the deviation is not intentional, it represents exactly the kind of undetected logic error most likely to distort a model's output without any visible sign — the same consequence class as R001, which is why it carries the same weight and critical-override status.
Related Articles
R001 — Hardcoded Cells
R001 (Hardcoded Cells) flags a formula cell that has been overridden by a typed numeric value, in a row where the surrounding cells otherwise share a clear, dominant formula pattern. It is critical severity, carries the highest weight of any FMAE rule (15.0), and is one of five critical-override rules under the SM-2.0 scoring methodology — meaning a single R001 finding caps the model's overall letter grade below A or B regardless of its numeric score.
R002 — Broken Links
R002 (Broken Links) flags a formula cell whose reference has broken — pointing at a deleted named range, a deleted worksheet, a reference-error cell, or an external workbook link the parser could not confirm resolves. It is critical severity and one of five critical-override rules under the SM-2.0 scoring methodology, meaning a single R002 finding caps the model's overall letter grade below A or B regardless of its numeric score.
R006 — Propagated Errors
R006 (Propagated Errors) flags any cell — formula or hardcoded — whose last calculated value is an Excel error (such as #REF!, #VALUE!, or #DIV/0!). Because an error value is a deterministic, unambiguous fact already present in the workbook, every R006 finding carries high confidence. R006 is critical severity and one of five critical-override rules under the SM-2.0 scoring methodology, meaning a single R006 finding caps the model's overall letter grade below A or B regardless of its numeric score.
FMAE Rule Taxonomy
Every rule in the FMAE structural rule pack declares a category attribute at the point it is defined in source — this is not a classification imposed on the rules afterward for documentation purposes, it is the classification the engine itself uses. Six categories cover all 26 rules — Structural (18 rules), Assumptions Governance (1), Integrity Controls (2), Structural Hygiene (1), Aggregation Logic (1), and Model Governance (3). This page publishes that taxonomy as the FMAE equivalent of a control catalog's classification scheme, cross-linked to the Rule Reference page for each member rule.
FMAE Scoring Engine — SM-2.0 Methodology
FMAE computes a model's risk score as 100 minus the triggered rules' combined weight, normalized against a fixed basis, currently 207.0 under the active SM-2.0 methodology. SM-1.0, the engine's original scoring basis (170.0, covering R001–R021), is retained as a frozen historical reference rather than deleted from the record. Five rules — R001, R002, R004, R006, and R023 — are critical-override rules. If any of them triggers, the resulting letter grade is capped so a model cannot be graded A or B regardless of how high its numeric score is. This page documents the exact formula, the versioning between SM-1.0 and SM-2.0, and a fully worked example.
Finding Data Model & Confidence
Every FMAE finding carries the same fixed structure — which rule triggered it and that rule's identity at the time it ran, its evidence, a narrative explanation, and a confidence label of high, medium, or low. Confidence is a deterministic categorical label derived from how strongly a row's cells agree on a pattern, not a machine-learning probability estimate. Stating this plainly matters, since describing FMAE's confidence as AI-derived or probabilistic would overstate what the engine actually does.
Formula Consistency in Financial Models
Formula consistency in a financial model means that cells in the same row or column that perform the same calculation use identical or structurally equivalent formulas. In a time-series financial model, the formula in the Year 1 column of a revenue line should be structurally identical to the formula in the Year 5 column of the same line, with references shifting as appropriate across periods. A cell that contains a formula materially different from its neighbours in the same row is either performing a different calculation intentionally (which should be documented) or contains an error introduced by manual editing.