Every answer and its explanation appears here once you have finished the path. Each one then links to the matching glossary entry, where the concept is set out in full with its worked example.
1. What is meant by the capacity of an insurance market?
The volume of risk the market can and will carry at a given time, set by its capital
Capacity is a volume of risk, not a number of players or a revenue figure. It depends on the capital available in the sector, players' appetite, funds coming from financial markets through insurance-linked securities, and the perceived profitability of the line. It is not fixed: it contracts after major losses that destroy capital and expands when results attract new money. For an emerging risk it often decides practical insurability: a risk that is insurable in theory but for which the market offers little capacity remains hard to cover at a reasonable price, and cyber long illustrated this.
Glossary entry →2. After the ransomware wave of 2020 and 2021, cyber premiums rise by several tens of percent and security requirements tighten; from 2023, the market softens. What is this movement called?
The underwriting cycle: a hard market, then a soft market
The insurance market alternates hard phases, where capacity becomes scarce, premiums rise and insurers become selective, and soft phases, where capacity is abundant and competition pushes prices down. A hard phase usually follows losses that erode capital or appetite; a soft phase comes when results attract new capital. The cycle also stems from the nature of the business: the true cost of a policy is only known afterwards, and prices adjust with a lag. Cyber went through a particularly sharp one, with abrupt tightening around 2020 and then easing as losses stabilized and capacity returned.
Glossary entry →3. At renewal, an underwriter starts from last year's premium and decides on a 5% increase. What reasoning flaw threatens this method?
Anchoring on the expiring premium, which repeats the error if the old price was wrong
Pricing a renewal as a change on the previous price, rather than from the cost of the risk, carries past errors forward: a premium 30% too low stays too low after a 5% increase. The mechanism has been known since Tversky and Kahneman's experiment published in Science in 1974: a rigged wheel stopped on 10 or on 65 before participants were asked the share of African countries in the UN, and median estimates were 25% for the first group and 45% for the second. A number unrelated to the question had moved the answer by twenty points. The expiring premium is a far stronger anchor, because it looks relevant.
Glossary entry →4. A cedant collecting 10 million euros of premium enters a 40% quota share treaty. What does it cede, and what does the reinsurer bear?
4 million of premium, and 40% of every claim in the book
The quota share is the simplest proportional treaty: reinsurer and cedant share premiums and losses at the same percentage. At 40%, the cedant cedes 4 million of premium and the reinsurer pays 40% of every claim, small or large. There is no threshold: the idea of a retention belongs to the other family, non-proportional reinsurance. A quota share lightens the cedant's balance sheet and increases its underwriting capacity, but it also gives away part of the good results, and it protects the top of the distribution no more than the bottom.
Glossary entry →5. A cedant is protected by an 8 million excess of 2 million layer. A claim costs 6 million. How much does the reinsurer pay?
4 million, the cedant keeping the first 2 as its retention
An excess of loss treaty is non-proportional: the reinsurer responds only above a threshold, the retention, and up to a limit. Here the cedant keeps the first 2 million and the reinsurer pays what exceeds it, within the 8 million limit: on 6 million, it pays 4. The 8 million is the limit, not a trigger, and percentage sharing belongs to the quota share. This treaty protects the top of the distribution without ceding small claims, and its price reads from the probability that the retention is reached.
Glossary entry →6. A pension fund puts 2% of its portfolio into an insurance-linked securities fund, invested in catastrophe bonds on Atlantic windstorm, Japanese earthquake and Australian cyclone. What is it looking for?
A return weakly tied to markets: its losses come from catastrophes, not the economy
Insurance-linked securities transfer insurance risk to capital markets, and catastrophe bonds are the typical example. An institutional investor gains access to the return on insurance risk outside reinsurers' balance sheets. What it mainly buys is decorrelation: a hurricane does not depend on the stock market. The investment is not riskless for all that: the principal is lost in whole or in part if the catastrophe occurs, and specialist funds went through years of significant losses, in 2017 and in 2022. The investor protects nothing it owns: it carries someone else's risk for a return.
Glossary entry →7. A catastrophe bond pays a total coupon of 8.7%, made of 3.1% collateral yield and a 5.6% risk spread. Its expected loss is 1.45%. What is its multiple?
About 3.9: the 5.6% spread over the 1.45% expected loss
The multiple divides the spread by the expected loss: it says how many times the technical risk is paid for. 5.6 divided by 1.45 gives about 3.9. Collateral yield does not enter the calculation: it pays for interest rates, not for risk. If short rates fall by 120 basis points and the spread does not move, the displayed coupon drops to 7.5% while the price of risk has not changed by a single basis point. Reading the total coupon as a price of risk thus confuses two markets. The multiple moves with the cycle: it falls when capital is abundant and years go by without a catastrophe.
Glossary entry →8. Ahead of a heavy hurricane season, a reinsurer opens a sidecar in which investment funds provide fully collateralized capacity. What risk does the collateral remove for the reinsurer it protects?
Credit risk: the money that will pay claims is already deposited
In collateralized reinsurance, the commitment is fully secured by a deposit, often provided by capital markets investors. The protected party therefore no longer depends on its reinsurer's solvency when the loss occurs: credit risk is what disappears. The catastrophe risk is still there, it has only changed hands, and the premium is still due. A sidecar lets a reinsurer absorb a heavy season without committing its whole balance sheet. The downside sits with the investor: as long as a season's claims are not settled, part of the collateral stays locked and cannot be redeployed.
Glossary entry →9. During Hurricane Irma in 2017, parametric catastrophe bonds on the Caribbean trigger on measured wind speeds, but several sponsors find that the amounts received differ markedly from their actual losses. What is this gap called?
Basis risk: the measured parameter does not perfectly track the actual loss
A parametric trigger pays on a physical measurement, here wind speed, not on the loss incurred. It is fast and not open to dispute, but it never fits the loss perfectly: an unusual track or an exposure spread differently from what the model assumes is enough to open a gap, in either direction. That is basis risk, and it stays with the sponsor. After Irma, these gaps fed a debate on preferring indemnity triggers in sovereign issues: slower, but faithful to the loss.
Glossary entry →10. Cyber catastrophe bonds exist, but their market remains narrow, in the hands of a few sponsors. Why is transferring cyber risk to capital markets harder than transferring windstorm?
Because cyber lacks a stationary physical model and an assured decorrelation from markets
The mechanics are the same as for windstorm: a vehicle issues securities, places the proceeds in collateral and gives up the principal only if the trigger is hit. What cyber lacks are two properties of natural perils. First, a stationary model: the technical environment rewrites itself within a few years, and different vendors' models diverge widely on attachment probability. Second, decorrelation, which gives the asset class its whole value: a systemic cyber catastrophe can hit the infrastructure of the markets themselves, and so the rest of the investor's portfolio at the same moment. Existing issues in fact rest on indemnity triggers, not parametric ones.
Glossary entry →