Handbook
AI Scenario Development Handbook
A practical guide to creating your own AI scenario
Service
ORX Scenarios
Community
ORX Scenarios Community
Risk programme
Management, Practice & Framework
Handbook - March 2024
In response to the increasing focus on AI as both an opportunity and a risk for the financial services industry, ORX Scenarios has published this AI Scenario Development Handbook to support institutions in developing or reviewing their own AI scenarios.
Based on data submitted by, and discussions with, ORX Scenarios subscribers, this handbook provides practical guidance on the development and assessment of AI scenarios as well as their preparation and governance.
The AI Scenario Development Handbook is available for free to all ORX Scenarios subscribers. The handbook provides the information you need to create a robust and effective scenario for AI events.
Scope and objectives
Forming part of a series of handbooks offering practical guidance on developing scenarios for challenging and emerging risk themes, this handbook, like others in the series, provides:
- Up-to-date data-driven scenario analysis guidance based on current AI operational risk scenario trends, offering a foundational baseline for scenario analysis supported by currently available industry data supplemented by ORX information.
- A comprehensively standardised view of current industry scenario data, with all key scenario components mapped to relevant ORX categorisations (event, causes, impacts, controls, drivers).
- Four full example scenarios covering the main storyline themes identified in the survey data submitted by ORX Scenarios subscribers.
How to use this report
Scenario practitioners can use this handbook and its two accompanying documents to:
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Understand and identify the thematic focus, storyline, and core components of an AI scenario against the industry’s most common components for this type of scenario, from causes and control failures to impacts and drivers (including impact-driver linkages)
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Build or review a full AI scenario, including its storyline and qualitative and quantitative components
![Assessment_Reversed Lime](https://orx.org/hs-fs/hubfs/Website/Icons/Lime/White%20lines/Assessment_Reversed%20Lime.png?width=1623&height=1856&name=Assessment_Reversed%20Lime.png)
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Leverage a range of current data on AI risk events within and outside the financial services industry, including five ORX News stories converted into AI scenario form
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![Ai Connections Ai Connections](https://orx.org/hubfs/Website/Images/Resource%20images/2024/Ai%20Connections.png)
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Contacts:
![Helen L’Abbate](https://orx.org/hs-fs/hubfs/Helen%20square.jpg?width=92&height=92&name=Helen%20square.jpg)
Helen L’Abbate
Deputy Director - Research & Information, ORX
![Simon Johnson](https://orx.org/hs-fs/hubfs/Simon%20Johnson%20B+W.jpg?width=92&height=92&name=Simon%20Johnson%20B+W.jpg)
Simon Johnson
Head of Services, ORX
![Robert Reay-Jones](https://orx.org/hs-fs/hubfs/Robert%20Reay-Jones.jpg?width=92&height=92&name=Robert%20Reay-Jones.jpg)
Robert Reay-Jones
Research Manager, ORX
![Mia Davies](https://orx.org/hs-fs/hubfs/Website/Images/Staff%20profile%20images/Mia%20Davies.jpeg?width=92&height=92&name=Mia%20Davies.jpeg)
Mia Davies
Junior Research Analyst, ORX