For CROs & Risk Officers
Credit, market, and operational risk sit in your framework as distributions, thresholds, and scenarios. Cyber usually sits beside them as a heat map. Üsta produces cyber exposure in the terms your framework already uses, so it can be governed, monitored, and reported like everything else.
Request a Scoping CallThe annual loss your organisation has a given chance of exceeding. The instrument from which a cyber risk limit is derived.
The Problem
Every other material risk class in your framework is quantitative, largely because the regulator has required it to be. Credit, market, and operational risk carry distributions, thresholds, and capital implications. Cyber guidance from central banks and supervisors has stayed qualitative, so cyber has stayed qualitative too.
That leaves the risk function holding a material exposure it cannot express in the language the rest of the framework runs on. A register entry scored amber cannot be aggregated, cannot be compared against another risk class, cannot anchor a limit, and cannot be trended in a way a risk committee can act on.
The gap is not awareness. Most risk functions know precisely what is missing. The gap is a defensible number, produced by a method that survives challenge from an auditor, a regulator, or a sceptical board member.
What loss figure should our cyber risk appetite threshold actually be?
How do we quantify cyber for our ORSA or ICAAP submission?
Our register scores cyber as high. High compared to what?
Which cyber scenarios are material enough to model separately?
How do we show the committee that exposure moved, and why?
What You Get
Cyber exposure as a full probability distribution, not a point estimate. The same shape of output your credit and operational risk models already produce.
Capital at risk at your chosen confidence level. The figure from which an enforceable cyber risk limit can actually be derived.
Data breach, ransomware, fraud, outage, and third-party failure modelled separately, each with its own frequency and severity parameters.
Which control domains are driving exposure, and what improving each one is worth in expected loss reduction.
Cyber exposure structured to sit alongside the other risk classes in ORSA, ICAAP, and FSCA Joint Standard reporting.
Every figure carries the evidence quality behind it. Self-attested inputs widen the band, corroborated evidence narrows it, and the model says which is which.
Why This Lands With Risk Functions
The frequency and severity modelling, the distributional assumptions, and the treatment of parameter uncertainty are the same apparatus used to price insurance and value long-tail liabilities. That matters because a risk function does not want a score. It wants to know what the model assumed, where the parameters came from, and how wrong the answer could be.
Every assumption is documented and open to challenge. Where evidence is thin, the output says so through a wider confidence band rather than a falsely precise number. You should be able to interrogate the method, not just receive the result.
Each scenario modelled separately, with its own frequency and severity parameters, so the drivers of the aggregate are visible rather than assumed.
Use Cases
Credit, market, and operational risk sit in your framework as quantified loss distributions. Cyber cannot until it is expressed the same way. Üsta produces the financial inputs that let cyber be governed alongside the risk classes that already have models, rather than in a parallel qualitative process.
A risk appetite statement gives direction; a limit tells you when you have breached it. Üsta gives you a loss distribution from which to derive a specific threshold, a VaR or expected loss figure your risk committee can monitor, report against, and recalibrate as control posture changes.
Regulators increasingly expect cyber to be treated with the same analytical seriousness as other material risks. Üsta produces documented, auditable exposure figures with the assumptions exposed, structured for submission and for the questions that follow it.
A register entry scored 'high' invites the obvious question: high compared to what, and on what basis? Üsta gives you an independent financial view to test register scores against, and to justify where cyber genuinely ranks against your other material exposures.
Model the scenarios that matter to your business individually rather than as a single aggregate cyber line item. Understand which ones drive the tail, and what a severe year actually looks like in financial terms.
Report cyber movement the way you report every other risk class: exposure this period against last, what drove the change, and what remains outside appetite. Üsta produces a defensible basis for that narrative rather than a maturity score that cannot be trended meaningfully.
We will assess fit and walk through how cyber exposure would slot into your existing risk framework and reporting cycle.