---
type: method
slug: business-risk-register
title: "Build an enterprise risk register"
category: "Legal, Risk & Compliance"
subcategory: "Risk management"
level: intermediate
source: https://deepstoryresearch.com/method/business-risk-register
publisher: Deepstory Research
---

> **How to use this file:** attach it to ChatGPT, Claude, Gemini or Copilot (or paste the prompt section), replace every [PLACEHOLDER] with your details, and add any data or Deepstory evidence files the method needs.

## When to use this method
- Board risk reviews.
- Insurance and investor diligence.

## Prompt

# Build an enterprise risk register
Method by Deepstory Research: deepstoryresearch.com/method/business-risk-register

You are a chief risk officer. Follow the method below step by step. Goal: A company-level risk register with categories, scores, owners, controls and appetite.

## My inputs
- Business: [BUSINESS]  (example: describe)
- Key concerns: [KEY_CONCERNS]  (example: list)
- Risk appetite: [RISK_APPETITE]  (example: low for compliance, medium for growth)

Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source.

## Steps to follow
1. Identify strategic, operational, financial, compliance and external risks.
2. Score inherent risk.
3. List existing controls and residual risk.
4. Assign owners and treatment plans.
5. Define KRIs.

## Deliver the output in this structure
- Risk register
- Heat map
- Treatment plans
- KRIs

## Quality rules
- Each risk has one owner.
- Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION.
- If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED].
- End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.

## Evidence you can attach
- Insured Catastrophe Losses: https://deepstoryresearch.com/data/catastrophe-losses (AI context file: https://deepstoryresearch.com/context/catastrophe-losses.md)
- Six-Economy Macro Baseline: https://deepstoryresearch.com/data/global-macro-baseline (AI context file: https://deepstoryresearch.com/context/global-macro-baseline.md)
- AI Regulation: Bills vs Laws: https://deepstoryresearch.com/data/ai-regulation-tracker (AI context file: https://deepstoryresearch.com/context/ai-regulation-tracker.md)
- Stablecoins & the GENIUS Act: https://deepstoryresearch.com/data/stablecoins-regulation (AI context file: https://deepstoryresearch.com/context/stablecoins-regulation.md)

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Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment matters need a qualified professional.