If I Were a CRO: The Risk Platform I Would Demand (Through the Lens of an Analyst)

Written by Michael Rasmussen

Published on2025-10-09Updated on2025-10-09DiscussionLeave a Comment on If I Were a CRO: The Risk Platform I Would Demand (Through the Lens of an Analyst)

Technology does not give you good risk management. Strategy does.

Risk is everywhere—and that’s not a problem. As I say on the Risk Is Our Business podcast, the organization that is not taking risk is already out of business. The job is not to eliminate risk; it’s to take the right risks, at the right time, with eyes wide open.

Yet too much of what passes for “risk management” is a compliance exercise. In the United States in particular, risk has been conflated with Sarbanes‑Oxley controls. Sufficient? Absolutely not. Managing issues and losses after the fact is like driving with your eyes glued to the rearview mirror. You might learn from what you hit, but you won’t avoid the next one.

In my workshops, one of the best summaries I’ve heard is: risk management’s role is to ensure there are no surprises in achieving objectives. I agree—and I’d go further. Risk management is about making better decisions. Not just reporting on whether prior decisions met their objectives.

On the podcast, we’ve explored this repeatedly—from Renee Murphy on the slipperiness of reputational risk and the poverty of metrics beyond financials, to guests who challenge the orthodoxy of defensive risk. Tony argued we should be risk seekers—strategically, not recklessly. I’m with him. The modern risk leader is less a “risk cop” and more a risk strategist and facilitator who enables the business to take calculated risk in pursuit of value. EY’s recent work on the risk strategist echoes this pivot.

So if I were the Chief Risk Officer—or advising one as I do daily—what would I require from a risk management platform? Below is my buyer’s manifesto, grounded in GRC 7.0 – GRC Orchestrate, infused with hard‑won lessons from client engagements and conversations on Risk Is Our Business.

TL;DR — The Non‑Negotiables

1. Model the business (strategy, objectives, value streams, processes, services, assets).
2. Performance & Objective Management comes first; risks live in that context.
3. Strategic Risk & Resilience (Decisions) risk as a strategy shaper.
4. Objective‑Centric ERM performance‑aligned, proactive, integrated.
5. Operational Risk & Resilience day‑to‑day reliability that enables strategy.
6. Risk Analysis, Aggregation & Visualization — distributions, not heat maps.
7. Risk Quantification that actually works (credible math, tested models).
8. Rich Visualization incl. bow‑tie, event/fault trees, loss exceedance.
9. Digital Twins of the enterprise and extended enterprise.
10. Scenario Modeling & Simulation war‑games, tabletops, stress tests.
11. Collaboration & Accountability owner, control owner, payer of risk.
12. Insurance & Risk Transfer integrated with quantification.
13. Risk Intelligence external/internal signals feeding foresight.
14. Integration with ERP/OPS/Cyber/TPRM/H&S/etc. via a data fabric & ontology.
15. Artificial Intelligence explainable, governed, and agentic as it matures.

First Principles: Strategy → Frameworks → Process → Then Technology

GRC 7.0 – GRC Orchestrate starts with the operating model, not the tool. The sequence matters:

1. Strategy & Governance. Clarify the mission, risk culture, decision rights, and the roles/responsibilities across business and risk functions. Risk belongs on the bridge, not in the boiler room.
2. Frameworks. Anchor in standards that emphasize objectives and uncertainty.
3. Processes. Define how sensing, analyzing, deciding, acting, and learning flow across the lines of the business.
4. Technology. Choose a platform that enables and orchestrates the above—not one that forces your organization to color inside its heat‑map lines.

If the platform can’t model how your business creates value and how decisions propagate through that model, it can’t help you manage risk — only inventory it, and those are most often out of date and of little value.

What I Would Demand From the Platform (and How I Would Test It)

1) Model the Business (Strategy → Value Streams → Processes → Assets → Obligations)

• Why it matters. Risk doesn’t float in the ether; it attaches to objectives, processes, services, products, vendors, locations, technology, and people.
• What good looks like. A native business architecture: objectives and KPIs/KRIs; value streams and processes (with owners); services; assets; third‑parties; and obligations mapped to each. A graph/ontology under the hood to keep relationships first‑class.
• Red flags to avoid. A flat risk register with custom fields pretending to be a model.
• Ask vendors. Show me a graph of how a change in a supplier’s risk posture propagates to service performance and strategic objectives in real time.

2) Performance & Objective Management (Context Before Risk)

• Why it matters. Objectives provide the frame for uncertainty. Starting with risk is starting in the middle, like putting the cart before the horse. This dovetails into #4 below.
• What good looks like. First‑class objectives with measurable KPIs, tolerance bands, and explicit linkage to risk, controls, scenarios, and initiatives. Ability to do objective‑level risk appetite and track risk‑adjusted performance.
• Red flags to avoid. “We support objectives”—but only as a picklist on a risk form.
• Ask vendors. Create a new strategic objective live. Link three KRIs, two initiatives, and a scenario. Now show me the risk‑adjusted forecast for that objective.

3) Strategic Risk & Resilience (Decisions)

• Why it matters. Risk doesn’t only protect strategy; it shapes it.
• What good looks like. A decision intelligence layer: option analysis, assumptions management, stress testing, and strategy simulations. Ability to quantify upside risk and optionality. Governance for how strategic decisions are logged, evidenced, and reviewed.
• Podcast tie‑in. We often highlight how boards fixate on downside while ignoring the risk of missed upside. “Risk seeking” (hat tip, Tony) lives here.
• Ask vendors. Demonstrate how the platform compares strategic options (build/buy/partner) using scenarios, quantification, and sensitivity analysis.

4) Objective‑Centric ERM

• Why it matters. ERM must be performance‑aligned, not control‑centric.
• What good looks like. Risks owned where work happens; KRIs/KPIs joined at the hip; near‑misses and weak signals captured and learned from; thematic risk aggregation that rolls from objective to objective, not from forms to forms.
• Red flags to avoid. Quarterly risk reviews that never change the plan.
• Ask vendors. Show me how a deteriorating KRI automatically triggers re‑forecasting of the objective and proposes mitigations with owners and funding.

5) Operational Risk & Resilience (ORM)

• Why it matters. Strategy rides on the rails of operations.
• What good looks like. Process‑level risks, controls, and impact tolerance mapped to important business services; automated controls & evidence where feasible; incident/near‑miss capture; playbooks tied to scenarios; resilience tests with learning loops.
• Ask vendors. Run a tabletop on a payment outage. Show me the stress on impact tolerances, customer outcomes, and the handoff to issue/cause/corrective action management.

6) Risk Analysis, Aggregation & Visualization (Distributions, Not Dots)

• Why it matters. Risk is not a color. Risk is a distribution over outcomes.
• What good looks like. Histograms, cumulative loss curves, tornado/sensitivity charts; correlation/aggregation that is explicit and explainable; ability to roll up by structure (org) and function (themes) without double counting.
• Red flags. A heat map as the main screen. Even worse, a stop light.
• Ask vendors. Quantify a scenario, show the distribution, and explain aggregation assumptions. Change an assumption; show sensitivity in real time.

7) Risk Quantification (Credible Math)

• Why it matters. Decisions require scale and trade‑offs.
• What good looks like. Transparent models (e.g., Monte Carlo where appropriate), parameter estimation from internal/external data plus expert judgment with credibility weighting; support for heavy tails; scenario libraries with calibration; model validation and versioning. I appreciate approaches like Graeme Keith’s work on robust estimation and aggregation—because they respect uncertainty rather than wish it away.
• Red flags. One‑size‑fits‑all scoring engines and black‑box “AI risk scores.”
• Ask vendors. Walk me through your model risk management: documentation, testing, drift monitoring, and auditability.

8) Risk Visualization (Make It Think & Feel)

• Why it matters. The right picture shortens the distance to a good decision.
• What good looks like. Bow‑tie analysis (causes/controls/consequences), fault and event trees, causal maps, control effectiveness cones, loss exceedance curves. Executive views that are decision‑forward, not dashboard‑pretty.
• Ask vendors. Build a bow‑tie live; link controls to testing/evidence and show how a failed test reshapes the consequence distribution.

9) Digital Twins (Of the Organization and the Extended Enterprise)

• Why it matters. You can’t simulate what you haven’t modeled.
• What good looks like. A living digital twin of your organization’s value streams, services, sites, suppliers, data, and dependencies. Twins support what‑if analysis: supplier outage, regulatory change, cyber event, demand surge. They learn as new data arrives. Twins extend to third parties and fourth parties via shared data and attestations.
• How it works in GRC 7.0. The twin is driven by a semantic graph/ontology; an orchestration engine sustains synchronization across systems (ERP, cyber, H&S, TPRM). Agentic AI can probe the twin with experiments, surface nonlinearities, and propose mitigations with cost/benefit.
• Ask vendors. Show me the twin of an important business service. Knock out a critical supplier. Quantify customer impact, regulatory exposure, and the mitigation portfolio with cost, time, and residual risk.

10) Scenario Modeling & Analysis

• Why it matters. Scenarios are the wind tunnel for strategy and operations.
• What good looks like. Stress and reverse stress testing; war‑gaming and tabletop exercises that are instrumented (evidence, timings, decisions); scenario trees with branching; Bayesian updating as facts accumulate; playbook linkage.
• Ask vendors. Run a geopolitical escalation scenario affecting logistics. Show the branching decisions, updated probabilities, and funding trade‑offs.

11) Collaboration & Accountability (Owner, Control Owner, Payer)

• Why it matters. Risk is everyone’s job but not no one’s job.
• What good looks like. Clear RACI across risk, control, and budget ownership (who pays for mitigations and residual risk). In‑flow collaboration for executives and frontline managers, not just risk staff. Human‑centered UX; mobile capture for incidents/near‑misses; conversation linked to decisions.
• Ask vendors. Assign an accountable executive, a control owner, and a payer to a mitigation. Route for approval; evidence funding and benefits realization.

12) Insurance & Risk Transfer

• Why it matters. Transfer is one lever in the portfolio.
• What good looks like. Policies, limits, exclusions, and claims data tied to scenarios and quant models; optimization of retain vs transfer; integration with brokers/insurers; evidence for insurability and premium negotiations.
• Ask vendors. Show me how cyber control maturity shifts expected loss and the optimal retention/limit selection.

13) Risk Intelligence (Foresight Beats Hindsight)

• Why it matters. External signals widen the field of view.
• What good looks like. Feeds for geopolitical, regulatory, macroeconomic, ESG/reputation, threat intel, and supplier signals. Signal ingestion → enrichment → triage → linkage to twins, objectives, and scenarios.
• Podcast tie‑in. Our episode on reputation underscored the gap between narrative risk and operational metrics. Intelligence connects the two.
• Ask vendors. Demonstrate how a negative media surge or sanction change flows into scenarios, KRIs, and decision options.

14) Integration (Data Fabric & Ontology, Not Spaghetti ETL)

• Why it matters. Risk sits at the seams.
• What good looks like. Open APIs, event streams, and connectors; a semantic layer so data lands meaningfully; identity integration for least‑effort adoption; low‑code mapping; lineage and quality checks.
• Ask vendors. Show the canonical ontology and how ERP incidents, SIEM alerts, vendor ratings, and HR data map to it—live.

15) Artificial Intelligence (Useful, Governed, and Agentic)

• Why it matters. AI amplifies sensing, analysis, and orchestration—if governed.
• What good looks like. ML for anomaly detection; NLP for unstructured evidence; copilots for authorship and decision support; agentic AI to run simulations, propose mitigations, and draft playbooks—with guardrails: model cards, bias/robustness testing, audit trails, human‑in‑the‑loop, and a clear RAIL/AI governance framework.
• Ask vendors. Explain how your AI is validated, how humans supervise it, and how you prevent model drift and hallucination from entering decisions.

What I Will Not Buy

• A static risk register with pretty heat maps.
  
• “Compliance‑first” risk that never touches objectives or decisions.
  
• Black‑box quantification with no model risk discipline.
  
• Dashboards that report but never re‑plan.
  
• AI without governance, provenance, or explainability.
  
• Integration that means CSVs and weekend heroes.

The GRC 7.0 – GRC Orchestrate Blueprint

Sense → Model → Decide → Act → Learn is the feedback loop. The platform should:

• Sense. Ingest internal telemetry and external intelligence.
  
• Model. Maintain the semantic graph and digital twins; keep them current.
  
• Decide. Run scenarios, quantify, compare options; document choices and rationale.
  
• Act. Launch initiatives, controls, transfers; assign owner/control owner/payer; fund and track benefits.
  
• Learn. Update models from outcomes, near‑misses, and after‑action reviews.

This is the bridge of the Enterprise—not a back‑office inbox.

A Concrete Walkthrough: Third‑Party Disruption to a Key Service

1. Signal. A high‑risk supplier’s financial health deteriorates; sanction chatter emerges.
   
2. Twin. The service twin shows a concentration risk to two geographies and a single alternate.
   
3. Objective link. Customer churn and revenue objectives flag increased variance.
   
4. Scenario. Branching: replace supplier (12–18 weeks), dual‑source (8–10 weeks), or stockpile (4 weeks) with cost/benefit quantified.
   
5. Visualization. Bow‑tie surfaces control gaps (QA on alternate supplier, logistics reroute).
   
6. Quantification. Monte Carlo + expert priors estimate loss exceedance; sensitivity highlights logistics lead time.
   
7. Decision. Executive review selects dual‑source + temp stockpile; payer funds expedited onboarding; insurance team evaluates trade‑credit cover.
   
8. Act & learn. Playbooks executed; KRIs monitored; post‑mortem updates priors and the twin.

Metrics That Matter (Beyond the Usual)

• Risk‑adjusted performance at the objective level.
  
• Loss exceedance probability at board‑relevant thresholds.
  
• Near‑miss capture and conversion to learning actions.
  
• Control effectiveness trajectory (not just pass/fail).
  
• Scenario coverage & currency (last run, last calibrated).
  
• Decision cycle time from signal to funded action.
  
• Reputation/experience indicators (customer & employee)—yes, Renee’s drumbeat.
  
• Insurance ROI (retained vs. transferred vs. mitigated)

RFP Prompts I Actually Use

• Modeling. Show me your semantic graph. What are the first‑class objects? How do relationships version over time?
  
• Objectives first. Create an objective, link KPIs/KRIs, attach scenarios—and quantify residual risk.
  
• Quant. Demonstrate parameter calibration from internal/external data and expert judgment with credibility weighting.
  
• Digital twin. Knock out a supplier in the twin; recompute service risk and objective variance.
  
• Decision log. Where do decisions live? How are assumptions captured and reviewed?
  
• AI governance. Provide model cards, validation evidence, and human‑in‑the‑loop controls.
  
• Integration. Map ERP incidents, SIEM alerts, and vendor ratings to your ontology—live.
  
• Accountability. Assign owner/control owner/payer; route approvals; show funding/budget links.

Final Word (and an Invitation)

Producing heat maps and generic lists to fulfill a reporting requirement is not risk management. The modern platform must help leaders make and fund better decisions—with context, quantification, accountability, and learning. That is the spirit behind GRC 7.0 – GRC Orchestrate, and the consistent theme on Risk Is Our Business.

If you’re wrestling with platform choices or shaping an RFP, I evaluate solutions constantly and carry a deep library of requirements. Reach out—and in the meantime, tune into the podcast for unvarnished conversations with leaders who are moving risk from the boiler room to the bridge.