The Risk Rating Formula
The standard qualitative formula used across ISO 31000-aligned programmes, COSO ERM, and most UK regulated-firm frameworks is:
// Standard risk rating formula
Risk Rating = Likelihood × Impact
On a 5×5 risk matrix, each axis is scored from 1 to 5. The product ranges from 1 to 25. Some organisations use a 1–10 scale on each axis (product range 1–100); the 5×5 model is the mid-market default because it is simple enough for boards to read and granular enough for triage.
Worked Example
Third-party data breach via a key supplier
- Likelihood: 3 (could occur once in the assessment period given current supplier controls)
- Impact: 4 (regulatory notification, client harm, reputational damage)
- Calculation: 3 × 4 = 12
On a common banding of 1–5 Low, 6–12 Medium, 13–25 High, a rating of 12 is Medium - warranting active monitoring and treatment planning, but not necessarily immediate board escalation unless net exposure or appetite thresholds say otherwise.
Where Risk Positions Come From: Financial and Non-Financial Matrices
The multiplication is the easy part. What actually determines whether a risk rating is defensible - and whether two assessors would score the same risk the same way - is what sits underneath the grid: your impact and likelihood matrices.
In a well-run ERM programme, risk positions (the gross and net likelihood × impact scores on the register) are not plucked from intuition. They are derived by scoring each risk against published matrices that define what each level means in practice. Most frameworks separate impact into two layers:
- Financial impact matrix - anchors each impact level to monetary bands sized to your organisation's materiality. For example: Level 1 = up to £50k residual loss; Level 2 = £50k–£250k; Level 3 = £250k–£1m; and so on. The exact thresholds should reflect your ICAAP, management reporting, or board materiality - not a generic template copied from a consultant deck.
- Non-financial impact matrix - describes operational, regulatory, conduct, and reputational harm at each level. Level 3 might mean "regulatory notification required, local supervisory interest"; Level 5 might mean "national enforcement action, franchise-level reputational damage, or loss of licence to operate". Without this layer, two risks can share the same impact score while one implies a manageable fine and another implies existential harm.
- Likelihood matrix - defines credible frequency bands in testable language: less than once in twenty years; once in ten years; multiple events within five years. This lets you compare owner assessments against incident history, loss data, and external benchmarks rather than debating what "unlikely" feels like.
When a risk owner scores impact as 4 and likelihood as 3, they should be able to point to the matrix row and say: "Impact 4 means £250k–£1m financial exposure plus regulatory notification; Likelihood 3 means we expect something in this category roughly once in the assessment period." That is what makes the resulting position - 12 on a 5×5 grid - explainable to a second-line challenger, an auditor, or a non-executive director.
Key Idea
The matrix is the output; the definitions are the input
A 5×5 heat map is a visual summary of positions already scored against your matrices. If the financial and non-financial bands are not written down, the positions float - and the rating is just a number with no ledger behind it. For how this connects to the visual layer boards see, see the 5×5 risk matrix and heat maps.
The same matrices apply whether you are setting a gross (inherent) position or a net (residual) position. The difference is the scenario you are scoring against: gross asks "how bad and how likely with no controls?"; net asks "how bad and how likely given controls as they actually operate?" Both positions should be traceable back to the same published definitions - otherwise gross and net scores become incomparable across risks and across quarters.
For judgement-based assessment, well-understood financial and non-financial matrices are what let a risk owner set a residual position directly and still defend it. For formula-based assessment, the matrices provide the anchor points the formula works from. Either way, the matrices are the foundation. For the four assessment approaches built on top, see how to assess enterprise risk.
Risk Rating Categories (Low, Medium, High)
After calculating the numeric rating, organisations map it to pre-defined bands. There is no single universal cut-off - firms define bands to match their risk appetite and reporting needs. A typical 5×5 banding looks like this:
| Band |
Score range |
Typical response |
| Low |
1–5 |
Accept and monitor; minimal active treatment unless appetite is very tight |
| Medium |
6–12 |
Managed within existing controls; treatment plans where net rating exceeds appetite |
| High |
13–25 |
Priority treatment, senior oversight, likely principal-risk or board visibility |
Some firms use five bands (Very Low through Very High) or split Medium into two tiers. That is fine - document the thresholds in your ERM framework and apply them the same way every quarter. The failure mode is not choosing 6–12 vs 6–15 for Medium; it is having no written definition at all, so every assessor invents their own cut-offs.
Gross vs Net Risk Ratings
A single risk usually carries two ratings, not one:
- Gross (inherent) rating - likelihood × impact before controls. Shows the raw severity of the risk.
- Net (residual) rating - likelihood × impact after controls, reflecting how controls reduce likelihood, impact, or both.
The gap between inherent and residual ratings is one of the most informative outputs in an RCSA or risk register review. A risk with inherent 20 and residual 6 tells a very different story to a risk with inherent 8 and residual 6 - even though both residual ratings are identical. For full definitions, see inherent vs residual risk vs appetite explained.
Common Pitfall
Rating net risk as if controls work perfectly
The most common rating error is scoring net risk based on control design rather than control performance. If a control has never been tested, or failed its last test, it should not fully reduce the net rating. Net ratings should reflect the control environment as it actually operates - which is why RCSA and control testing are linked, not separate exercises.