Run faster, better-documented climate risk assessments with AI
A cohort-based online course for risk and sustainability teams at banks, insurers and asset managers. You learn to use AI assistants at each step of a climate risk assessment, from data gathering to scenario analysis and disclosure drafting, with the documentation and oversight supervisors expect, and you apply it to a portfolio of your own.
AI-assisted Climate Risk Assessment for Financial Institutions
For analysts and managers who run, review or commission climate risk work: risk, credit and underwriting teams, sustainability and ESG teams, and the model validation and data teams who support them. You need working knowledge of climate risk concepts; you do not need to code.
- Supervisors no longer ask whether you analyse climate risk; they ask whether it is integrated into risk management and decisions, as FINMA Circular 2026/1 and the EBA ESG risk guidelines now require.
- Climate risk work is data-heavy and document-heavy: hazard data, counterparty locations, transition plans, scenario variables and disclosure drafts. AI assistants can take on much of that work.
- Used without method and governance, AI produces numbers no one can explain. The course teaches where AI helps, where it does not, and how to document it so a validator can follow it.
Three parts, one assessment of your own portfolio
Six modules
One step of the assessment each week
Live clinics
Weekly case clinic with Artamis faculty
Applied project
An AI-assisted assessment of one segment of your own portfolio
Six modules, following the Climate Risk Decision Ladder
Each module takes one step of a climate risk assessment, shows where an AI assistant helps and where human judgement must stay, and ends with a worked template you apply to your own portfolio.
M1What supervisors expect, and where AI fits
By the end of this module you can:
- Read FINMA Circular 2026/1, the EBA ESG risk guidelines and IFRS S2 as a sequence of capabilities
- Locate your institution on the Climate Risk Decision Ladder
- Separate tasks AI can assist from judgements that must stay with people
M2Exposure at scale (R1)
By the end of this module you can:
- Geo-reference collateral and counterparties with AI-assisted matching
- Combine public hazard data such as Copernicus and WRI Aqueduct with your book
- Check data licences and set quality rules before analysis starts
M3Vulnerability and scenarios (R2)
By the end of this module you can:
- Extract targets and capex plans from counterparty transition plans, with citations
- Choose decision-relevant NGFS scenarios and match horizons to tenors
- Distinguish exposures to support through transition from those to reduce
M4Financial translation (R3)
By the end of this module you can:
- Use AI assistants to build and document a scenario-adjusted PD/LGD or pricing calculation
- Prove translation on two material segments with the model owners
- Reconcile climate-adjusted results to baseline and state the limits
M5Governing AI in climate risk work (R4)
By the end of this module you can:
- Classify your use cases under the EU AI Act and FINMA Guidance 08/2024
- Design oversight points, evaluation sets and reproducibility records
- Write model documentation a validator can review without reconstruction
M6From analysis to disclosure and decisions (R4–R5)
By the end of this module you can:
- Draft disclosure narrative from approved sources, with every figure traceable
- Keep disclosure and internal risk reporting on the same analysis
- Put results in front of credit, underwriting and investment teams in the tools they use
An AI-assisted assessment of your own portfolio
You take one material segment of your institution’s portfolio through the workflow from the course, and leave with a documented assessment and the governance pack to run it again. You may anonymise data and use ranges.
- Exposure and vulnerability view for one segment, with data sources and quality checks recorded
- A financial translation with the method, assumptions and limits documented
- An AI use-case record: classification, oversight points and evaluation results
- A one-page summary for your risk committee
How you complete the course
| Module checks | A short knowledge check at the end of each module |
|---|---|
| Live clinics | Attend at least four of six, or review the recordings and submit the clinic exercise |
| Applied project | Submitted and reviewed by Artamis faculty against a published rubric |
Built on Artamis frameworks
- The Climate Risk Decision Ladder: the sequence from exposure to steering
- The Sustainable Intelligence Stack: data, analytics, governance and talent
- The Artamis Responsible AI in Sustainable Finance Compliance framework
- Practice on realistic portfolio cases
A certificate of completion from Artamis Academy with CPD hours. The course is a practical entry point to the AISFC professional certification.
More than a certificate
- A documented, AI-assisted climate risk assessment of one segment of your portfolio
- Workflow templates for each step, from exposure mapping to disclosure drafting
- A governance pack: use-case record, oversight design, evaluation set and documentation skeleton
- Practice cases built on realistic portfolios
Choose how you take it
Join the waitlist
Places and founding-cohort terms are offered to the waitlist first
On request
Several participants from one institution, with a shared applied project on your portfolio
On request
Delivered to your teams, with cases and data from your institution
The course is in development. Dates and fees are announced to the waitlist first.
Taught from the inside
Led by Artamis founder Diana Díaz Castro, formerly a Programme Supervisor at the UN Environment Programme Finance Initiative, where she led the creation of the Net-Zero Insurance Alliance and other global initiatives. Faculty bring current advisory work with insurers, banks, asset managers and development finance institutions, with guest practitioners in specialist sessions.
Frequently asked
Do I need to code?
No. You use AI assistants through their standard interfaces; where code is produced, you learn to specify, check and document it.
Which AI tools does the course use?
General-purpose AI assistants available to most institutions. The method is tool-neutral, and Artamis does not sell an AI platform.
Can I use my institution’s data?
Yes, for the applied project, under your institution’s data policies. You may anonymise data or use a sample.
How does it relate to AISFC?
It goes deep on one workflow, climate risk assessment. AISFC is the broader professional certification on AI across sustainable finance.
Training a team in AI-assisted climate risk assessment?
Private cohorts use cases from your own institution and end with a capstone readout to management. Tell us how many people you would like to certify.