Supercharge your risk management with AI:
DO MORE WITH LESS RESOURCES
Learn how to streamline risk management tasks, master AI applications in live workshops, and apply insights directly to your work.
Transform your Risk Management with AI in 5 Weeks
Transform your Risk Management with AI in 5 Weeks
Transform your Risk Management with AI in 5 Weeks
Slow and manual risk management processes make your team exhausted?
Too many emerging risks to investigate them all?
Risk reporting takes so much time, no time left for integrating into decision making?
Always wanted to do quantitative risk analysis but don’t know where to start?
Too many emerging risks to investigate them all?
Risk reporting takes so much time, no time left for integrating into decision making?
Always wanted to do quantitative risk analysis but don’t know where to start?
To stay competitive, you need to superpower your risk team.
With AI, you can automate repetitive tasks, quickly analyze data, and uncover insights that give you a strategic advantage.
In just 5 weeks, this course will show you how to integrate AI into your risk management workflow to save time, reduce errors, and improve quality and relevance of risk analysis.
With AI, you can automate repetitive tasks, quickly analyze data, and uncover insights that give you a strategic advantage.
In just 5 weeks, this course will show you how to integrate AI into your risk management workflow to save time, reduce errors, and improve quality and relevance of risk analysis.
Slow and manual risk management processes make your team exhausted?
Too many emerging risks to investigate them all?
Risk reporting takes so much time, no time left for integrating into decision making?
Always wanted to do quantitative risk analysis but don’t know where to start?
To stay competitive, you need to superpower your risk team.
With AI, you can automate repetitive tasks, quickly analyze data, and uncover insights that give you a strategic advantage.
In just 5 weeks, this course will show you how to integrate AI into your risk management workflow to save time, reduce errors, and improve quality and relevance of risk analysis.
Alex Sidorenko, Your RiskTech Mentor
Alex is an experienced executive across strategic, investment and operational risks and insurance working within multibillion dollar corporations in Australia, GCC and Europe. Currently a Group Head of Risk, Insurance and Internal audit at Serra Verde. Successfully integrating quantitative risk analysis into decision making, procurement, project management, budgeting, planning and performance management. Alex is an expert in applying AI for risk identification, quantitative risk analysis, stress testing and risk based decision making. Alex built and published a popular risk management chatbot RAW@AI, regularly used by risk managers all over the world http://riskacademy.ai/.
Saved more than $13 million per year in premiums on cargo and PD/BI insurance through industry leading quantitative risk analysis without changing deductibles or limits. Which got him named FERMA Risk Manager of the year 2021. Successfully presenting corporate risk profile at the Ministry of finance and helping secure more than $1B in extra funding.
Author of the most popular free risk management book in the world, more than 150K downloads in 3 languages. Risk manager of the year, FERMA, 2021, Best international ERM case 2021, RIMS. Risk manager of the year, RUSRISK, 2014, Best ERM Implementation, RUSRISK, 2014, Best risk management training FERMA 2024, RUSRISK, 2013, 2014, 2015, finalist in risk management awards in 2018 and 2019.
Author of the most popular free risk management book in the world, more than 150K downloads in 3 languages. Risk manager of the year, FERMA, 2021, Best international ERM case 2021, RIMS. Risk manager of the year, RUSRISK, 2014, Best ERM Implementation, RUSRISK, 2014, Best risk management training FERMA 2024, RUSRISK, 2013, 2014, 2015, finalist in risk management awards in 2018 and 2019.
Alex Sidorenko, Your RiskTech Mentor
Alex is an experienced executive across strategic, investment and operational risks and insurance working within multibillion dollar corporations in Australia, GCC and Europe. Currently a Group Head of Risk, Insurance and Internal audit at Serra Verde. Successfully integrating quantitative risk analysis into decision making, procurement, project management, budgeting, planning and performance management. Alex is an expert in applying AI for risk identification, quantitative risk analysis, stress testing and risk based decision making. Alex built and published a popular risk management chatbot RAW@AI, regularly used by risk managers all over the world http://riskacademy.ai/.
Saved more than $13 million per year in premiums on cargo and PD/BI insurance through industry leading quantitative risk analysis without changing deductibles or limits. Which got him named FERMA Risk Manager of the year 2021. Successfully presenting corporate risk profile at the Ministry of finance and helping secure more than $1B in extra funding.
Author of the most popular free risk management book in the world, more than 150K downloads in 3 languages. Risk manager of the year, FERMA, 2021, Best international ERM case 2021, RIMS. Risk manager of the year, RUSRISK, 2014, Best ERM Implementation, RUSRISK, 2014, Best risk management training FERMA 2024, RUSRISK, 2013, 2014, 2015, finalist in risk management awards in 2018 and 2019.
Author of the most popular free risk management book in the world, more than 150K downloads in 3 languages. Risk manager of the year, FERMA, 2021, Best international ERM case 2021, RIMS. Risk manager of the year, RUSRISK, 2014, Best ERM Implementation, RUSRISK, 2014, Best risk management training FERMA 2024, RUSRISK, 2013, 2014, 2015, finalist in risk management awards in 2018 and 2019.
how AI empowers your team
This course is built around real-world tasks, not theory. In hands-on workshops, you’ll learn to automate processes, analyze risks, and create AI-driven reports. With powerful AI tools, even a small team can handle tasks at a scale previously achievable only by large departments. With step-by-step guidance from experienced trainers, you’ll gain confidence in applying AI to your risk management tasks from day one.
how AI empowers your team
This course is built around real-world tasks, not theory. In hands-on workshops, you’ll learn to automate processes, analyze risks, and create AI-driven reports. With powerful AI tools, even a small team can handle tasks at a scale previously achievable only by large departments. With step-by-step guidance from experienced trainers, you’ll gain confidence in applying AI to your risk management tasks from day one.
- Work with AI tools live,
completing real-world risk management tasks - Receive expert instruction,
on automating reporting, analyzing risks, and using AI for decision-making - All lessons are practical,
no deep technical knowledge required
AI Increases Risk Management Efficiency by 40%
Research from top institutions, including Harvard and MIT, shows that AI can boost productivity by 40%. This course will help you harness that power in your risk management processes.
Who this Course is for
-
Risk Managers
Seeking to enhance their methods with AI-driven analysis and reporting. -
Mid-to-Senior Executives
Looking to streamline decision-making under uncertainty -
Audit, Compliance, and Security Professionals
Aiming to automate data analysis and improve reporting efficiency. -
Analysts
Those new to AI who want to enhance their quantitative risk assessment skills.
Who this Course is for
-
Risk Managers
Seeking to enhance their methods with AI-driven analysis and reporting. -
Mid-to-Senior Executives
Looking to streamline decision-making under uncertainty -
Audit, Compliance, and Security Professionals
Aiming to automate data analysis and improve reporting efficiency. -
Analysts
Those new to AI who want to enhance their quantitative risk assessment skills.
Course Format
Live Online Workshops – 5 Weeks
15-minutes call with each participant before the course start to personalize the learning experience
Course Format
Live Online Workshops – 5 Weeks
15-minutes call with each participant before the course start to personalize the learning experience
€1950 for a risk team (up to 3 people)
950 for a single person. Act now to secure this training in your corporate budget.
Ready to Supercharge Your Risk Management with AI?
Enroll now and get an AI-powered "team member" to automate tasks and enhance your decision-making in just 5 weeks!
Course Program
Course Program
Detailed Course Program
- Case-study: “How a Global Retailer Transformed Product Launch Decisions Using LLM-Powered Risk Insights”. Learn how a major retailer used GenAI to generate risk assessments on new product lines in record time, aligning internal knowledge with external market data.
- Why GenAI for risk and decision-making
- Quick overview of large language models (LLMs): their capabilities and common pitfalls, key differences.
- Real-world benefits: faster risk insight generation, more transparent decision-making, and deeper organizational learning.
- Building your core GenAI system
- What is a GenAI system: LLM choice + prompting strategy + company knowledge (RAG) + knowledge extraction technology + output format.
- Key prompting techniques and setting up custom instructions and system prompts to ensure accurate, decision-focused outputs (correct risk terminology and risk-based thinking).
- Laying the groundwork for responsible usage
- Data privacy and compliance considerations when feeding company data to LLMs.
- Setting up robust governance (e.g., approval flows, version control) so GenAI recommendations remain aligned with business objectives.
- Case-study: Spotting Tomorrow’s Threats Today: Is your company prepared for new EU AI regulation or the next regulation? How automated LLM-driven monitors help detect shifts in regulation trends months before they hit mainstream news.
- AI-driven risk governance
- Using GenAI RAG to build a risk management knowledgebase.
- Using GenAI for risk management governance documentation development (policies, procedures, limits, guidelines) and integrating into existing procedures.
- Automating risk-related workflows: how to use APIs to integrate GenAI outputs into existing governance tools and risk software.
- Automating horizon scanning and emerging risk detection
- Building custom agents or RAG systems to monitor internal and external data sources to identify emerging risks.
- Using GenAI for identifying and mapping potential risks on business decisions, contracts, budgets, projects and subsidiaries.
- Case-study: Turning Numbers into Narratives: How a Global Manufacturer Modeled Commodity Price Shocks Using LLM Prompts. How a manufacturing company used GenAI to develop intuitive probability distributions for metal prices—without employing a full-time quant.
- GenAI-assisted distribution modeling
- Using LLMs to represent uncertainties and risks as probability distributions, without deep statistical expertise.
- Generating “what-if” scenarios in minutes: how system prompts and RAG expedite iteration and reduce manual modeling.
- Simulations and scenario generation for non-quants
- Today anyone can run simulations, aggregate risks and calculate risk metrics (correlations, VaR, cVaR, p50, p80 and others) using GenAI.
- Easy methods to present ranges, confidence intervals, and tail risks in dashboards or interactive tools.
- Case-study: From Confusion to Confidence: A Financial Services Firm’s Transformation of Risk Training with GenAI Bots. Learn how an organization slashed onboarding times and boosted compliance by deploying an AI-based chatbot that answers policy questions instantly.
- Creating tailored reporting and decision support
- Designing system prompts and custom instructions for generating succinct, audience-specific risk briefs (e.g., executive board vs. project team).
- Leveraging multi-agent systems to produce multiple report formats simultaneously (one agent writes narratives, another creates data visualizations).
- Scaling risk culture and training with GenAI
- Building interactive training modules or chatbots to foster organization-wide awareness of risk-based thinking.
- RAG-enabled knowledge repositories to instantly answer “risk” queries (e.g., policy clarifications, mitigation trade-offs, insurance risk controls, cyber risk controls).
- Empowering employees to make better decisions
- Guiding business units in day-to-day decisions with integrated GenAI prompts (e.g., procurement, project management).
- Setting up a self-service systems where staff can explore uncertainties and trade-offs with minimal risk of misunderstanding.
- Case-study: One Brain, Many Departments: b2a2x model. How cross-functional AI collaboration enabled near-instant risk assessments on budgeting, procurement, and product launches, all under one governance umbrella.
- Developing GenAI solutions for other departments
- Tailoring prompts and instructions to each domain (procurement, budgeting, product launch) so they consider uncertainty and volatility.
- Building targeted applications that embed risk-based logic in everyday decisions (e.g., budget allocations, vendor selection).
- Advanced multi-agent orchestration
- Designing collaborative AI systems that coordinate across departments, tying risks to operational metrics.
- Using API calls for real-time data sharing and synergy among different LLM-driven agents.
- Practical deployment
- Participants apply each module’s lessons to a real scenario from their own company, drafting an end-to-end GenAI-driven risk solution.
- Show how a small team or solo manager can provide an enterprise-grade, decision-centric risk management service.
Detailed Course Program
- Case-study: “How a Global Retailer Transformed Product Launch Decisions Using LLM-Powered Risk Insights”. Learn how a major retailer used GenAI to generate risk assessments on new product lines in record time, aligning internal knowledge with external market data.
- Why GenAI for risk and decision-making
- Quick overview of large language models (LLMs): their capabilities and common pitfalls, key differences.
- Real-world benefits: faster risk insight generation, more transparent decision-making, and deeper organizational learning.
- Building your core GenAI system
- What is a GenAI system: LLM choice + prompting strategy + company knowledge (RAG) + knowledge extraction technology + output format.
- Key prompting techniques and setting up custom instructions and system prompts to ensure accurate, decision-focused outputs (correct risk terminology and risk-based thinking).
- Laying the groundwork for responsible usage
- Data privacy and compliance considerations when feeding company data to LLMs.
- Setting up robust governance (e.g., approval flows, version control) so GenAI recommendations remain aligned with business objectives.
- Case-study: Spotting Tomorrow’s Threats Today: Is your company prepared for new EU AI regulation or the next regulation? How automated LLM-driven monitors help detect shifts in regulation trends months before they hit mainstream news.
- AI-driven risk governance
- Using GenAI RAG to build a risk management knowledgebase.
- Using GenAI for risk management governance documentation development (policies, procedures, limits, guidelines) and integrating into existing procedures.
- Automating risk-related workflows: how to use APIs to integrate GenAI outputs into existing governance tools and risk software.
- Automating horizon scanning and emerging risk detection
- Building custom agents or RAG systems to monitor internal and external data sources to identify emerging risks.
- Using GenAI for identifying and mapping potential risks on business decisions, contracts, budgets, projects and subsidiaries.
- Case-study: Turning Numbers into Narratives: How a Global Manufacturer Modeled Commodity Price Shocks Using LLM Prompts. How a manufacturing company used GenAI to develop intuitive probability distributions for metal prices—without employing a full-time quant.
- GenAI-assisted distribution modeling
- Using LLMs to represent uncertainties and risks as probability distributions, without deep statistical expertise.
- Generating “what-if” scenarios in minutes: how system prompts and RAG expedite iteration and reduce manual modeling.
- Simulations and scenario generation for non-quants
- Today anyone can run simulations, aggregate risks and calculate risk metrics (correlations, VaR, cVaR, p50, p80 and others) using GenAI.
- Easy methods to present ranges, confidence intervals, and tail risks in dashboards or interactive tools.
- Case-study: From Confusion to Confidence: A Financial Services Firm’s Transformation of Risk Training with GenAI Bots. Learn how an organization slashed onboarding times and boosted compliance by deploying an AI-based chatbot that answers policy questions instantly.
- Creating tailored reporting and decision support
- Designing system prompts and custom instructions for generating succinct, audience-specific risk briefs (e.g., executive board vs. project team).
- Leveraging multi-agent systems to produce multiple report formats simultaneously (one agent writes narratives, another creates data visualizations).
- Scaling risk culture and training with GenAI
- Building interactive training modules or chatbots to foster organization-wide awareness of risk-based thinking.
- RAG-enabled knowledge repositories to instantly answer “risk” queries (e.g., policy clarifications, mitigation trade-offs, insurance risk controls, cyber risk controls).
- Empowering employees to make better decisions
- Guiding business units in day-to-day decisions with integrated GenAI prompts (e.g., procurement, project management).
- Setting up a self-service systems where staff can explore uncertainties and trade-offs with minimal risk of misunderstanding.
- Case-study: One Brain, Many Departments: b2a2x model. How cross-functional AI collaboration enabled near-instant risk assessments on budgeting, procurement, and product launches, all under one governance umbrella.
- Developing GenAI solutions for other departments
- Tailoring prompts and instructions to each domain (procurement, budgeting, product launch) so they consider uncertainty and volatility.
- Building targeted applications that embed risk-based logic in everyday decisions (e.g., budget allocations, vendor selection).
- Advanced multi-agent orchestration
- Designing collaborative AI systems that coordinate across departments, tying risks to operational metrics.
- Using API calls for real-time data sharing and synergy among different LLM-driven agents.
- Practical deployment
- Participants apply each module’s lessons to a real scenario from their own company, drafting an end-to-end GenAI-driven risk solution.
- Show how a small team or solo manager can provide an enterprise-grade, decision-centric risk management service.
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Copyright © 2024 RAW@AI
Copyright © 2024 RAW@AI