Description

A focused course, tailored for you

Cyber Risk Quantification for Advisory Consultants

Turn security findings into dollar-range risk statements that CFOs, CROs, and boards accept.

Your client's heat map has three red boxes. The CFO's question is: what does each one actually cost us? The framework gap list does not answer that. This course gives you the methodology to produce a defensible dollar range for every finding you bring to a client risk committee.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

The hardest moment in a cybersecurity advisory engagement is not the technical assessment. It is the slide that has to justify a control investment to a CFO who did not study threat modeling. Heat maps, maturity ratings, and gap counts describe the problem. They do not answer the questions boards actually ask: how much does a breach in our environment cost, which risks are worth spending on first, and how much does each control investment reduce our expected loss. The FAIR model answers all three, but applying it to real client data, without access to the client's internal loss history, using interview-derived estimates that survive actuarial scrutiny, is a skill most advisory teams learn slowly and inconsistently. This course gives you the systematic method.

What you walk away with

Build a defensible FAIR-based risk model from client interview data and existing control documentation.
Produce Monte Carlo simulation outputs a client risk committee accepts without technical translation.
Deliver a board-ready risk register with ranked scenarios, dollar ranges, and control investment recommendations.
Align a NIST CSF 2.0 gap assessment directly to a quantified risk model so both deliverables reinforce each other.
Structure CRQ outputs that satisfy DORA quantitative reporting requirements for financial sector clients.

The 12 modules

Module 1. FAIR Model Foundations for Consulting Engagements

The Factor Analysis of Information Risk model gives you a consistent structure for any client's threat scenario library. This module builds the full taxonomy: threat event frequency, vulnerability conditions, loss event frequency, and primary loss magnitude. You work through three client-archetype scenarios, building the input assumptions from first principles rather than industry averages, so the output survives a CFO's first question about where the numbers came from.

Module 2. Interview Protocol: Extracting Usable Data from Client SMEs

Most CRQ projects stall at data collection because the client's subject matter experts give qualitative answers to quantitative questions. This module gives you a structured interview guide and a facilitation technique that converts 'medium risk' into a calibrated estimate with a defensible confidence interval. You practice the pivot from 'how often does this happen?' to 'give me your best and worst year in the last five.'

Module 3. Control Effectiveness Mapping to Loss Reduction

Client controls do not appear in standard FAIR inputs as checkbox items. This module shows you how to translate a control set covering identity, detection, and response into resistance factors that modify threat event frequency and loss magnitude. You map a sample NIST CSF Protect function control set to three risk scenarios, producing the 'what this control is actually worth' answer your client needs for investment prioritization.

Module 4. Monte Carlo Simulation: Inputs, Outputs, and Presentation

A Monte Carlo simulation of a risk scenario produces a loss exceedance curve, not a single number. This module covers how to set up the simulation parameters, how to interpret the 10th and 90th percentile outputs, and how to present annualized loss expectancy to a non-technical risk committee without triggering the 'this looks made up' objection. Includes a worked financial sector scenario with documented assumptions.

Module 5. Building the Board-Ready Risk Register

The deliverable your client's board sees is not a model; it is a register with ranked risk statements, dollar ranges, and recommended control investments. This module gives you the register template, the ranking methodology, and the narrative format that positions each risk as a business decision. You build a six-scenario register from your module 3 control mapping and module 4 Monte Carlo outputs.

Module 6. NIST CSF 2.0 Gap Assessment Integration

When your engagement includes a framework gap assessment alongside a CRQ, the two deliverables must align. A gap in the Detect function should appear in the risk register as a specific increase in loss event frequency. This module covers the mapping between CSF 2.0 subcategories and FAIR risk factors, so your gap assessment feeds the quantification model directly rather than sitting in a separate slide deck.

Module 7. DORA Quantitative Requirements for Financial Sector Clients

The Digital Operational Resilience Act requires financial entities to quantify ICT risk as part of their risk management framework. This module covers the quantification obligations under DORA, the regulatory technical standards specifying the evidence your client needs, and how to structure a CRQ output that satisfies both the regulator and the client's internal risk appetite statement without producing two separate and contradictory models.

Module 8. Third-Party and Supply Chain Risk Quantification

Client CISOs consistently underestimate third-party risk because they lack the data. This module gives you the assessment protocol for extracting usable risk inputs from vendor questionnaires, third-party audit reports, and incident history without access to the vendor's internal systems. You build a tiered supplier risk scenario set and integrate it into the client's enterprise risk register as a distinct but connected risk category.

Module 9. Cyber Insurance Alignment: What Underwriters Actually Want

Clients who bring their CRQ output to a cyber insurance renewal expect it to reduce their premium. Underwriters want loss scenarios tied to specific perils, not framework gap counts. This module covers the scenario types underwriters price, the evidence package they accept, and how to frame your client's CRQ model output as a submission that materially improves coverage terms and reduces the insurer's back-and-forth requests.

Module 10. Communicating Uncertainty to CFOs and Risk Committees

A range of $3.2M to $18.7M annualized loss is accurate. It is also the number a CFO will challenge. This module gives you the framing techniques for communicating probabilistic outputs to deterministic thinkers: the expected versus tail distinction, the 'what moves the range down' question, and the use of scenario sensitivity analysis to show which assumptions the committee should actually care about.

Module 11. Iterating the Model Through the Engagement Lifecycle

A CRQ model built at the start of an engagement should update as the engagement progresses and client controls change. This module covers the version-control approach for a living CRQ model, the trigger conditions for re-running the simulation, and the format for a quarterly risk posture update that clients can present to their board without commissioning a new advisory engagement each cycle.

Module 12. Building the Client-Ready CRQ Deliverable Package

The final deliverable from a CRQ engagement is not a spreadsheet. This module walks through the complete package: the executive summary with risk-ranked scenarios and investment recommendations, the technical appendix with model assumptions and sensitivity analysis, and the board presentation with one slide per risk that a non-technical director can read in under two minutes. Includes the client handoff checklist for sustaining the model after engagement close.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

The client partner asks for a dollar figure behind the heat map finding; the gap list cannot produce one.

The CFO's first question is where the numbers came from; the model inputs are not documented.

The control investment recommendation has no quantified return; the budget ask stalls at committee.

The DORA examiner asks for quantitative ICT risk evidence; the framework gap assessment alone does not satisfy it.

What you get with this course

12 structured modules covering FAIR model mechanics through board-ready deliverable production
Downloadable risk register template, interview guide, Monte Carlo input template, and executive summary format
DORA quantitative requirement mapping for financial sector client engagements
NIST CSF 2.0 to FAIR risk factor crosswalk for gap assessment integration
Hand-built implementation playbook tailored to your client mix and engagement type
Access to the learning environment within 24 hours of purchase

What you will have in hand by Day 1, Week 1, Month 1

Access to the learning environment and all downloadable templates within 24 hours of purchase.

Hand-built implementation playbook delivered alongside course access, tailored to your advisory engagement type.

Before and after

Before

The engagement closes with a heat map and a list of control gaps. The client knows they have problems; they do not know which ones to fund first or what a breach in their environment actually costs.

After

The engagement closes with a ranked risk register, a dollar-range justification for each priority control investment, and a model the client can update quarterly. The budget conversation moves from 'we have red findings' to 'here is the expected loss reduction from this spend.'

What happens if you do not address this

Without quantification, advisory findings compete for budget on the same terms as every other IT cost: gut feel and political weight. Clients who receive a heat map and a gap list are left to quantify the risk themselves, or they do not, and the investment case loses to a competing ask from someone who can produce a number.

Who it is for

Cybersecurity advisors and engagement managers at professional services firms who run client-facing risk assessments and need to present findings in financial terms that CFOs, CROs, and boards accept. You understand control frameworks. You need a systematic methodology for turning control gaps into dollar-range risk statements that drive investment decisions.

Who this is NOT for. Internal security team leads who own the client's controls directly. This course is built for the advisory relationship, where the consultant must produce a credible quantification without operational access to the client's loss history or internal systems. It is also not designed for pure penetration testers or red team operators.

How it arrives

Text-based course in the Art of Service learning environment, plus downloadable templates and worked examples for every module, plus the hand-built implementation playbook delivered alongside course access.

Time investment. Approximately 8 to 12 hours for the full course, plus template application time per engagement. Most advisors work through modules 1 through 6 first and apply them to a live client engagement before completing modules 7 through 12.

Why $199 is the right number

Quantification model training courses cover the theoretical framework but do not address the client-facing delivery workflow specific to consulting engagements. Standard cybersecurity framework training covers control structure but not the quantification methodology that produces dollar-range risk statements. This course fills the gap between model theory and deliverable-ready consulting output.

FAQ

Do I need a statistics background to apply the FAIR model?

No. The course covers the model inputs, interpretation, and client-facing presentation without requiring statistical theory. The Monte Carlo simulation runs in a downloadable template; you configure the inputs and read the output.

Does this apply to clients outside financial services?

Yes. The FAIR model and the delivery framework apply to any client environment. The DORA module is specific to financial sector clients; all other modules use multi-sector scenarios applicable to advisory engagements across industries.

How long does a full CRQ engagement typically take to deliver?

The course gives you a structured delivery timeline for a standard six-scenario CRQ with full client workshops. The module 11 iteration approach shortens subsequent model updates to two to three weeks without restarting the engagement from scratch.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.