Try RAW@AI, probably the best risk management AI assistant on the planet RISK-ACADEMY Blog

RAW@AI offers risk management and quantitative risk assessment support to help you make informed decisions. Our AI-powered set of tools simplifies complex risk management tasks, saving you time and effort. RAW@AI can do your research, identify risks, write perfect risk descriptions, break down complex risks and suggest mitigations, write risk management policies, quantify risks and run monte carlo simulations, create agenda for risk interviews and workshops. More functionality is added every month.

Grow your risk team by having a virtual risk manager who is very well researched in probability theory, risk management standards, decision science and behavioural economics for a price of a lunch.

RAW@AI was named finalist in FERMA Risk Management Awards 2024! Get expert insurance advice and manage risks efficiently with RAW@AI.

RAW@AI – This is our primary assistant for answering general risk management questions, providing guidance on methodologies, risk identification, quantitative risk analysis, and conducting research. It’s focused on promoting decision-centric risk management (RM2) and leveraging neuroscience, probability theory, and practical case studies to support decision-making processes. You can use this assistant to dive deep into how to approach a risk from a business decision-making standpoint, or for advice on how to apply quantitative methods to real-world problems or how to integrate risk based thinking into procurement, operations or any other business process.

Identify Risks – This tools can identify risks relevant to you decision, contract or project based on the context you provide, industry and location. The model has been pre-trained on 3 out of 20 possible risk identification methods that show best performance for AI risk identification.

Risk Description Generator – This tool assists in creating detailed risk descriptions for use in reports, decisions, or for specific business cases. It helps ensure your descriptions reflect actual loss events, identify root causes, provide historical incidents and references.

Risk Mitigation Generator – This tool helps you break down each risk into potential root causes and identify potential mitigation strategies including real life case studies. Use this tool brainstorm risk mitigation strategies before you speak to risk owners.

Risk Policy Generator – This tool helps generate risk policies that are aligned with your organization’s objectives and compliant with ISO31000 and COSO ERM​. It ensures policies are integrated into existing business processes, making risk management a critical and actionable part of decision-making. Use this tool to create or refine your organization’s risk management policy, ensuring it is clear, documented, and linked to decision-making processes.

Here are some practical tips and tricks for prompting effectively within the context of decision-centric risk management:

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• Ask questions like you would to a junior risk manager: Start with simple, clear questions, then follow up for more details or clarification. If the initial response lacks depth, ask for further explanation or specifics.
• Don’t settle for the first answer: If the first response isn’t useful or thorough, keep probing. Follow up with specific requests for data, examples, or alternative perspectives.
• Reframe the question if needed: If the AI provides a repeated or irrelevant response, try rephrasing the question or adding more context to guide the answer toward what you need.
• Provide context: The more background you give, the better the answers will be. Context about the decision, assumptions, or the specific business area can drastically improve the relevance of the response.
• Be explicit about decision-making needs: Specify what you’re looking for—whether it’s assumptions, scenarios, potential outcomes, or risk impacts—rather than expecting a broad or vague response.
• Challenge vague responses: If the response is too generic, ask for specific metrics, numbers, or case studies. Don’t hesitate to push back on responses that don’t add actionable value.
• Force a deeper dive: Use prompts like “What are the key assumptions behind this?” or “Explain the reasoning behind this suggestion.” This encourages a more detailed and thoughtful response.
• If the AI repeats answers, redirect the question: If the conversation seems stuck, try a different angle or explicitly ask for new information that hasn’t been addressed before.
• Ask for examples: To clarify abstract concepts or advice, ask for real-life examples or case studies to make the response more practical and actionable.
• Use iterative prompting: Start with a high-level question and gradually drill down. For example, after getting a basic answer, ask for “the next level of detail” or “additional factors that may affect the outcome.”
• Maintain focus on the decision: When the AI starts giving theoretical responses, redirect the conversation back to the practical decision you’re making.
• Be patient and persistent: Sometimes it takes a few rounds to get the perfect response, especially on complex risk management topics. Don’t be afraid to ask again.