# Risk Quantification for Better Decisions | SwissGRC®

> RiskQuant von Swiss GRC simuliert aus dem Risikoregister bis zu 100'000 Szenarien und stellt die aggregierte Verlustverteilung der Risikotragfähigkeit gegenüber. Das Board Risk Reporting bereitet das Ergebnis für Entscheide von Verwaltungsrat und Geschäftsleitung auf.

- URL: https://swissgrc.com/en/risk-quantification/
- Publisher: SwissGRC®
- Published: 2026-06-11
- Last updated: 2026-10-07

## Key facts

- RiskQuant berechnet bis zu 100'000 Szenarien aus dem bestehenden Risikoregister und aggregiert sie zu einer Verlustverteilung.
- Die Simulation von bis zu 100'000 Durchläufen dauert laut Seite weniger als 500 Millisekunden.
- RiskQuant bietet mehr als 15 Verteilungen, darunter Normal, Lognormal, PERT, Gamma, Weibull, Triangular und Poisson, inklusive Compound-Verteilungen für Häufigkeit und Schaden.
- Abhängigkeiten zwischen Risiken werden mit Copulas modelliert, damit sichtbar wird, was bei gleichzeitigen Verlusten geschieht.
- Das Board Risk Reporting umfasst fünf Ansichten: Overview, Solvency & Capacity, Risk Drivers, Dependency Network und Decision Log.
- Im Beispiel der Seite nutzt das aggregierte Risiko 69 Prozent der Risikotragfähigkeit von CHF 9'004'940, die Reserve beträgt CHF 2'814'940.

# Uncertainty becomes a decision.

RiskQuant computes up to 100'000 scenarios from your risk register, aggregates them into a loss distribution and sets them against your company's risk-bearing capacity.

Contact us See Board Risk Reporting

Cyber incident *Lognormal* Key personnel *PERT* Technology failure *Gamma* Currency risk *Triangular*

Aggregated loss distribution, copula correlated n = 0

Expected loss

CHF0

Rare year (P95)

CHF0

Risk-bearing capacity

CHF9'004'940

Capacity used

0%

Trusted by leading organisations

Why now

## From estimates to evidence

In Switzerland and across Europe, the expectations of risk management are shifting: away from isolated assessments, towards a connected picture that captures dependencies and aggregated exposure.

**Your existing assessments already carry the expertise.** You only need the engine that turns frequency and severity into a robust number, and the translation that shapes it into a board decision.

That is exactly what RiskQuant is: production-ready quantification plus a board reporting that answers the right question.

#### From low, medium, high to a range

Instead of three levels, the full span of possible outcomes, each risk with its matching distribution.

LognormalGammaPERTTriangularWeibull

#### Dependencies instead of single risks

Copula-based correlation shows what happens when several losses arrive at the same time.

CopulaCorrelation matrixStress

#### No new model, no double maintenance

RiskQuant computes with the data that is already in your risk register.

up to 100k in < 500msVaRCVaR

What sets RiskQuant apart

## Board Risk Reporting: a number becomes a decision

A board decides on budget, reserves, insurance and on which residual risk it consciously bears. RiskQuant translates the simulation into exactly that language. Five views, one continuous run.

Overview . Management Summary

### One statement in two sentences, not a chart

The board page leads with a clear statement instead of a histogram: expected loss CHF 3.38M, in 95 percent of scenarios below CHF 6.19M, in the worst one percent above CHF 7.61M. The statistics are there, but they do not force themselves on you.

Directly below it, the board's three levers as **Insights for the Board**: reserve, insurance and consciously borne residual risk, each with a concrete franc amount.

*RiskQuant . Overview*

![RiskQuant Overview with Management Summary and Risk Exposure](https://swissgrc.com/wp-content/uploads/2026/07/rq-overview.webp)

Solvency & Capacity

### Risk against capacity

Aggregated risk against risk-bearing capacity, with a concrete franc amount instead of a traffic-light colour. The aggregated risk uses 69 percent of capacity, headroom CHF 2'814'940. The position lies clearly within capacity, the probability of insolvency below 1 percent (around 1 in 417 years).

The real message for the board is the trend: **the value at risk is rising.** Bearable today, worth watching tomorrow.

*RiskQuant . Solvency & Capacity*

![RiskQuant Solvency and Capacity, risk against capacity over time](https://swissgrc.com/wp-content/uploads/2026/07/rq-capacity.webp)

Risk Drivers

### Three risks drive two thirds

Not every risk carries the same weight. The simulation shows where the expected loss really comes from, sorted by contribution. The three largest drivers together account for 68 percent. This is exactly where the board's attention turns first.

- Technology failure, around 23 percent
- Loss of key personnel, around 23 percent
- Cyber incident, around 22 percent
- Tail risk and mitigation visible per driver

*RiskQuant . Risk Drivers*

![RiskQuant Risk Drivers, concentration and top drivers by contribution](https://swissgrc.com/wp-content/uploads/2026/07/rq-drivers.webp)

Dependency Network

### Risks do not move alone

Losses rarely occur in isolation. RiskQuant models, copula-based, which risks move together and which move in opposite directions. Single assessments become a connected picture, the foundation of every robust aggregation.

*RiskQuant . Dependency Network*

![RiskQuant Dependency Network, connections between risks](https://swissgrc.com/wp-content/uploads/2026/07/rq-network.webp)

Decision Log

### The decision is part of the report

Resolution, rationale and the derived measures are recorded directly on the same run. In the example accepted within risk appetite, with a measure and a deadline, next review in the following quarter. On the next run you see not only the new numbers, but also what was last decided and whether it worked.

This turns reporting into a **traceable, auditable governance trail**.

*RiskQuant . Decision Log*

![RiskQuant Decision Log with resolution, rationale and measures](https://swissgrc.com/wp-content/uploads/2026/07/rq-decision.webp)

Quantitative core

## Built for enterprise risk quantification

Everything it takes to move from qualitative assessments to production-ready Monte Carlo simulation. Powerful behind the scenes, clear and traceable in the board reporting. The same engine also feeds the drivers back into your familiar Risk Landscape, the heatmap as a reality check.

#### 15+ distributions

Normal, Lognormal, PERT, Gamma, Weibull, Triangular, Poisson and more, including compound distributions for frequency and severity.

#### Dependency patterns

Model whether risks stay independent, move together under stress, or arrive simultaneously in severe scenarios.

#### up to 100k simulations in < 500ms

Vectorised engine, built for speed. Full portfolio simulations in real time, not as an overnight batch.

#### Stress test

See which risks drive extreme scenarios. Contribution analyses beyond a freely selectable stress threshold.

#### Expected Value, VaR and CVaR

Expected loss, Value at Risk and Conditional VaR, translated into reserve, transfer and consciously borne residual risk.

#### Auditable trail

Every run, every assumption and every resolution stays traceable. Governance where decisions are made.

Quantitative engine from our partner

## Frequently asked questions

### Was ist RiskQuant von SwissGRC?

RiskQuant ist eine Lösung zur Risikoquantifizierung mit Monte-Carlo-Simulation. Sie rechnet mit den Daten aus dem Risikoregister und liefert zusätzlich ein Board Risk Reporting für Entscheide.

### Braucht RiskQuant ein separates Risikomodell?

Nein. RiskQuant rechnet mit den Daten, die bereits im Risikoregister liegen. Dadurch entsteht kein neues Modell und keine doppelte Pflege.

### Welche Kennzahlen liefert RiskQuant?

RiskQuant liefert Expected Loss, Value at Risk und Conditional VaR. Diese Werte werden in Reserve, Risikotransfer und bewusst getragenes Restrisiko übersetzt.

### Wie zeigt RiskQuant Abhängigkeiten zwischen Risiken?

RiskQuant modelliert Abhängigkeiten mit Copulas und stellt sie im Dependency Network dar. Zusätzlich lassen sich Stresstests mit frei wählbarem Schwellenwert durchführen.

### Wie werden Entscheide im Reporting nachvollziehbar?

Im Decision Log werden Beschluss, Begründung und abgeleitete Massnahmen direkt am gleichen Simulationslauf festgehalten. Jeder Lauf, jede Annahme und jeder Beschluss bleibt so nachvollziehbar und prüfbar.