Insurance-Linked Securities Education

Where the capital markets meet catastrophe risk

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Welcome to ILS101

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Course Curriculum

A structured learning journey through insurance-linked securities, climate risk, cyber exposure, and parametric insurance.

Core Programme

The ILS Series

9 lectures covering the full spectrum of insurance-linked securities — from fundamentals to sovereign risk management.

01 Why Risk Transfer is so Important
The economic and social value of catastrophe risk transfer and how it underpins the ILS market.
FoundationsRisk Transfer
Go to lecture
02 What are ILS Part 1 — Catalyst, Market Data, Cat Bond Structure & Term Sheet
The catalyst behind the ILS market, key market data, and a deep dive into cat bond structures and term sheets.
Cat BondsStructures
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03 What are ILS Part 2 — Sidecars, CRe, ILWs & Weather Derivatives
Beyond cat bonds: sidecars, collateralised reinsurance, industry loss warranties, and weather derivatives.
SidecarsILWs
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04 What are ILS Part 3 — Advantages of ILS, Uncorrelated, Losses & Spreads
Why ILS is attractive to investors: low correlation, historical losses, and spread analysis.
InvestorsReturns
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05 What are ILS Part 4 — Triggers and How They Work
Indemnity, parametric, modelled loss, and industry loss triggers — how each works and when they pay out.
TriggersPayouts
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06 ILS Pricing Part 1
Key variables influencing cat bond pricing models, expected loss, and risk premiums.
PricingExpected Loss
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07 ILS Pricing Part 2
Advanced pricing, secondary market valuation, and spread dynamics.
Secondary MarketValuation
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08 Why (Re)insurers Use ILS
How insurers and reinsurers use ILS for capital relief, diversification, and risk management.
CedantsCapital Relief
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09 Sovereign Disaster Risk Management
How governments and NGOs use cat bonds and risk pools for resilience funding.
Sovereign RiskDevelopment
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Specialist

Specialist Series

Deep dives into climate science, cyber risk, and parametric insurance. Audio episodes available now, full lecture series coming soon.

The Climate Series

How our evolving climate shapes catastrophe risk, from SSTs and ENSO to CMIP6 projections.

Climate Fundamentals — Full Episode
Audio episode available
Full lecture series in development — coming soon

The Cyber Series

Explore the emerging asset class — from threat landscapes and underwriting to cyber cat bonds and systemic risk.

5 lectures covering cyber threats, underwriting, aggregation, reinsurance, and capital markets — coming soon

The Parametric Series

Triggers, payout structures, sovereign pools, basis risk, and the future of parametric insurance.

Parametric Insurance — Full Episode
Audio episode available
2 lectures in development — coming soon
Supporting

Supporting Series

Additional modules to complement your ILS education.

The Fixed Income Series

Insurance capital structure, subordinated debt, Solvency II, RT1/AT1 instruments, and credit spread analysis.

Coming soon

The Regulator Series

Rating methodologies from S&P, Moody's and AM Best. Capital adequacy, risk-based models, and governance.

Coming soon

Lecture Library

Select a lecture to begin learning

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Shorts

Short-form audio episodes covering key ILS topics. Listen in-browser or download.


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Industry Reports

Research and market analysis from leading insurance and reinsurance institutions.

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Factsheet Library

Download our educational resources on Insurance-Linked Securities

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Climate Data Centre

Sea surface temperatures are a key driver of Atlantic hurricane activity and catastrophe bond pricing. Use these tools to explore live climate data.

Why SSTs Matter

Warmer ocean surfaces provide the energy that fuels tropical cyclones. SST anomalies in the Atlantic Main Development Region (MDR) are one of the strongest predictors of hurricane season severity.

ENSO & Hurricane Activity

El Niño events increase vertical wind shear over the Atlantic, suppressing hurricane formation. La Niña does the opposite — reduced shear allows more storms to develop and intensify.

ILS Market Relevance

Cat bond spreads widen ahead of hurricane season and tighten afterwards. Monitoring SSTs and ENSO phases helps ILS investors assess whether seasonal hurricane risk is above or below average.

ENSO Phase Timeline

El Niño years (red) tend to suppress Atlantic hurricanes via increased wind shear, while La Niña years (blue) remove that brake — leading to more and stronger storms. Notice how the most active Atlantic hurricane clusters (late 1990s–2000s, 2020–2022) coincide with La Niña phases. ILS investors track ENSO forecasts closely: a La Niña outlook can widen cat bond spreads months before hurricane season begins.

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Source: NOAA Climate Prediction Center ONI (Oceanic Niño Index) classification.

ENSO Phase vs Atlantic Storm Activity

La Niña years average significantly more Atlantic named storms than El Niño years, consistent with reduced wind shear favouring cyclogenesis. ENSO phase classified by NOAA ONI during peak hurricane season (JAS/ASO).

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Sea Surface Temperature Analysis

Source: NOAA OISST V2.1 via Climate Reanalyzer, University of Maine

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Sea Surface Temperature Analysis

Source: NOAA OISST V2.1 via Climate Reanalyzer, University of Maine

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Current Year SST Anomaly

This chart shows how much warmer or cooler the ocean surface is compared to the long-term average (1982–2011). The highlighted line represents the selected year's daily anomaly: values above zero (shaded red) mean the ocean is warmer than normal, values below zero (shaded blue) mean cooler than normal. Background lines show the previous decade for context.

Why it matters: Tropical cyclones draw energy from warm ocean water. When SSTs run persistently above the climatological mean — especially in the Atlantic Main Development Region during hurricane season (Jun–Nov) — storms can form more easily and intensify more rapidly. Anomalies of +0.5°C or more are considered significant and often feature in seasonal hurricane outlooks from CSU and NOAA.

For ILS investors: Sustained positive anomalies heading into hurricane season signal elevated expected loss, which can pressure cat bond spreads wider and increase reinsurance pricing at mid-year renewals.

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Source: NOAA Optimum Interpolation SST V2.1 (OISST), via Climate Reanalyzer, University of Maine. Anomaly = selected year daily SST minus 1982–2011 climatological mean.

What the Students Say

Reviews from students of an ILS educational course co-founded and led by Toby Pughe, spanning the global (re)insurance and capital markets industry.

Where the alumni are based

Disciplines Represented

The alumni span every corner of the (re)insurance value chain

Course Director

TP

Toby Pughe

Founder, ILS101

Toby co-founded and delivered the Fundamentals of Insurance-Linked Securities course, training professionals from leading (re)insurers, investment managers, rating agencies, regulators and sovereign risk pools worldwide. He has since launched ILS101 as a dedicated platform to make ILS education more accessible.

Currently working at an investment manager in London, Toby has deep experience across catastrophe bonds, (re)insurance and ILS portfolio management.

The statistics and reviews on this page reflect students of an ILS educational course that Toby Pughe co-founded and led. Individual names and identifying details have been withheld pending updated consent for this platform.

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Module Assessments

Choose Quick Quiz (10 random questions) to practice, or Full Assessment to earn your certificate. Score 70%+ to download your certificate.

Leaderboard

Top 20 scores per module from all users.

Glossary

Search ILS, credit, and cyber terminology.

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Natural Catastrophe Explorer

Explore historical hurricane tracks and global earthquake activity.

Why Track Hurricanes?

Atlantic hurricanes are the single largest driver of cat bond losses. Tracking historical tracks, intensities, and landfalls helps ILS investors calibrate their risk models.

Earthquake Risk & ILS

Japan, California, and New Zealand earthquakes have triggered cat bonds. Seismic risk is modelled using fault databases, historical catalogues, and ground motion models.

From Data to Pricing

Cat modellers use event catalogues like these to build occurrence exceedance probability curves, which feed directly into cat bond attachment and exhaustion point calibration.

Data source: NOAA National Hurricane Center, HURDAT2 (Atlantic hurricane database). This data is provided by NOAA and is in the public domain. Use of this data does not imply endorsement by NOAA. For official forecasts and warnings, visit nhc.noaa.gov.

Recent Significant Earthquakes

Magnitude Distribution

Data source: USGS Earthquake Hazards Program FDSN Event Web Service. Data is provided by the U.S. Geological Survey and is in the public domain. Use of this data does not imply endorsement by USGS. For official seismic hazard information, visit earthquake.usgs.gov.

Hurricane Season Comparison

Compare two Atlantic hurricane seasons side by side. Select years and click Compare to fetch HURDAT2 data for both seasons.

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