Illustrative: the exceedance probability of a hazard as a sheet, return-period isolines and simulated events

Risk Academy, led by the Nexus Consortium · Course catalogue · Finance and Economics

Insurance and Actuarial Science

Actuarial science

Actuarial science, taught twice over: as the working methods of the field and as its frontier since 2024, with labs on the Academy's tools, open data and the Nexus Standards.

Core course Frontier course

The discipline

01Core course · L2 Intermediate

Actuarial science: foundations and practice

This area covers the quantitative methods of insurance and pensions: loss distributions, extreme value methods, dependence, credibility with sparse data, mortality and longevity, capital models and pricing under a changing climate, with validation of the models used.

Level
L2 Intermediate
Study time
about 24 hours (planning estimate)
Status
In authoring
Prerequisites
An L1 course in the area, or an entry review

Why now

Updates the reference longevity assumptions used for pension, annuity and reserving calculations. Institute and Faculty of Actuaries, CMI news, 1 March 2026

Learning outcomes

  1. Define loss distribution and the other key terms of the discipline and use them correctly in a written case
  2. Explain loss distributions and extreme value methods with a worked example and its source
  3. Apply the discipline's method to a documented case and explain each result with its source
  4. Analyse a named case against dependence and correlation, stating evidence, date and limits

Modules

  1. Loss distributions
    • Loss distributions
    • Extreme value methods
    • Dependence and correlation
  2. Credibility and sparse data
    • Credibility and sparse data
    • Mortality and longevity
    • Capital and solvency models
  3. Pricing under climate change
    • Pricing under climate change
    • Quantitative model validation
  4. Lab: the discipline's method
    • A policyholder's own claims history is informative but noisy; Bühlmann credibility weights it against the portfolio rate by the number of years observed and by the ratio of within-risk noise to between-risk variation.
    • Work the method through a documented case and explain each result
    • Read the method's sources and stated values

Labs with Academy tools

Nexus Standards

Teaches

  • NRS-F3 Insurance, catastrophe risk and protection gaps
  • NRS-M1 Method fabric: Universal mathematics and statistics
  • NRS-M9 Method fabric: Insurance and reinsurance

Relies on

  • NS-1 The UNI and the artefact catalogue
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)
  • NRS-C1 Risk vocabulary and ontology
  • NRS-C2 Risk assessment method
  • NRS-C3 Hazard, exposure, vulnerability and capacity data
  • NRS-C4 Risk data model, identifiers and exchange
  • NRS-C8 Evidence, uncertainty and provenance
  • NRS-C9 Risk models, methods and validation

Assessment

  • 40%Lab recordWork the discipline's method through a documented case and explain each result with its source and date
  • 40%Case memoApply the discipline's methods to a named place or organisation, stating evidence and limits
  • 20%Key terms checkShort answers on the key terms, marked against the definitions

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Intermediate, 4 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

References

  1. Institute and Faculty of Actuaries, CMI news, 1 March 2026
  2. Bühlmann, Experience rating and credibility, 1967
  3. Bühlmann and Gisler, A course in credibility theory and its applications, 2005
02Live map

Activity and exposure in the Gulf of Mexico coast

Night-time lights and population, a proxy for economic activity, with the floods and fires that put assets at risk, over the Gulf of Mexico coast.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 2

Activity and exposure

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

Activity and exposure, framed on the Gulf of Mexico coast.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONETSources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • Optional layers (4 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026

03How learning runs

How learning runs, as a process you can run

Select a scenario and press Play: course, pathway, practice, faculty, cells and record.

04What is changing

Frontier course · L3 advanced, programme courses and standards

Actuarial science: frontier methods

The methods, data, tools and studies that changed actuarial science between 2024 and 2026, taught by reproducing them on open data.

Level
L3 Advanced
Study time
about 28 hours (planning estimate)
Status
Planned
Prerequisites
Actuarial science: foundations and practice; Working knowledge of a scripting language (Python or R) for the labs

Why now

Updates the reference longevity assumptions used for pension, annuity and reserving calculations. Institute and Faculty of Actuaries, CMI news, 1 March 2026

Learning outcomes

  1. Explain what changed in actuarial science since 2024 and cite the studies, data or rules behind each change
  2. Reproduce CMI 2025 mortality projections model released on open data and state the uncertainty of the result
  3. Evaluate a 2024 to 2026 study: its question, data, method, limits and what it changes for practice
  4. Design an analysis that combines a frontier method with the faculty's instruments, and justify each choice

Modules

  1. CMI 2025 mortality projections model released
    • The Continuous Mortality Investigation released CMI 2025, calibrated to England and Wales data to end-2025, giving cohort life expectancy at 65 about eight weeks higher for males and six for females than CMI 2024.
    • Updates the reference longevity assumptions used for pension, annuity and reserving calculations.
    • Institute and Faculty of Actuaries, 1 March 2026
  2. Actuaries warn climate models understate economic risk
    • The Institute and Faculty of Actuaries and University of Exeter argue widely used climate-economy models show negligible GDP impacts, and that without action the global economy could lose 50% of GDP between 2070 and 2090.
    • Challenges actuaries to use tail-focused, plausible-worst-case scenarios when modelling climate risk.
    • Institute and Faculty of Actuaries, 16 January 2025
  3. IAIS adopts the Insurance Capital Standard
    • The IAIS adopted the Insurance Capital Standard, a globally comparable risk-based measure of capital adequacy for internationally active insurance groups and the quantitative element of ComFrame.
    • Sets a common basis for valuation and capital calculation that actuaries in large groups must implement and validate.
    • International Association of Insurance Supervisors, 5 December 2024
  4. Reproduction lab
    • Extend the discipline's method with one frontier method and compare its results
    • State the uncertainty and the limits of the result
    • Peer review against a shared checklist
  5. Technology that helps and the risks it carries
    • AI models, tokenisation and regulatory technology.
    • Model risk, cyber accumulation, exposure to quantum attacks on cryptography, and concentration on third-party cloud providers.

Labs with Academy tools

Nexus Standards

Teaches

  • NRS-F3 Insurance, catastrophe risk and protection gaps
  • NRS-M1 Method fabric: Universal mathematics and statistics
  • NRS-M9 Method fabric: Insurance and reinsurance

Relies on

  • NS-1 The UNI and the artefact catalogue
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)
  • NRS-C1 Risk vocabulary and ontology
  • NRS-C2 Risk assessment method
  • NRS-C3 Hazard, exposure, vulnerability and capacity data
  • NRS-C4 Risk data model, identifiers and exchange
  • NRS-C8 Evidence, uncertainty and provenance
  • NRS-C9 Risk models, methods and validation

Assessment

  • 50%Method reproductionReproduce one frontier method on open data and state the uncertainty of the result
  • 30%Study reviewA critical review of a 2024 to 2026 study: question, data, method, limits, what it changes
  • 20%Peer reviewReview two other learners' reproductions against a shared checklist

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Expert, 5 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

References

  1. Institute and Faculty of Actuaries, CMI news, 1 March 2026
  2. Institute and Faculty of Actuaries, Planetary Solvency – finding our balance with nature, 16 January 2025
  3. International Association of Insurance Supervisors, Insurance Capital Standard (ICS Level 1 and Level 2 texts), 5 December 2024
  4. Bühlmann, Experience rating and credibility, 1967
  5. Bühlmann and Gisler, A course in credibility theory and its applications, 2005
05Take part

Take part in the work

Start from who you are.

06Questions

Questions, answers and key terms

Is the course free?
Yes. Every course and learning material of Risk Academy, led by the Nexus Consortium, is free to study, self-paced or with a cohort. Ordinary participation has no fee; paid work, internships and fellowships are separate arrangements.
What does completing a course give me?
A completion record: the course, its version, the date and what was assessed, private by default and shared by you. It stacks into discipline, department and programme achievements. A record states what was studied and assessed and does not certify competence; it is not a licence, a professional title or an employment status.
Where do the data and the places come from?
Every faculty teaches on a twin of a real place built from open data; each layer carries its provider, licence and date, and every result on the Academy states its source. Maps and figures are indicators for teaching, never an assessment of a place.
How do I take part beyond the course?
Form a competence cell of three to seven people, study a shared pathway, take a supervised assignment in the National Working Groups, or bring a cohort from your institution. For organisations.

Key terms

Term

Loss distribution

A probability distribution of the size or total of losses over a period.

Term

Copula

A function that describes dependence between variables separately from their individual distributions.

Term

Credibility theory

Methods that blend a risk's own experience with wider data according to how reliable each is.

Term

Tail value at risk

The average loss in the worst cases beyond a chosen percentile.

ReportsContribute

Contribute evidence from this page.

Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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