The Credibility Report
Edition 24: Flood, Cat Bonds, and Infrastructure-Led Cyber Risk
Aon flags rising flood and drought risk, Zurich returns to the cat bond market with $150m Turicum Re, Tower Hill upsizes Winston Re to $375m at lower pricing, At-Bay reports ransomware shifting toward VPN and remote-access exploitation, with refined arXiv and journal sections on geography-driven MTPL modelling, ActuBench, biological age, Tweedie exposure treatment, and graph-based categorical embeddings.
Welcome to Edition 24. This week is a useful reminder that “soft market” does not mean “low risk.” Capital is still plentiful in catastrophe markets — Zurich returned to cat bonds with a $150m Turicum Re issue, while Tower Hill upsized Winston Re to $375m at lower pricing — but the underlying risk signals are getting messier: Aon’s 2026 climate work points to rising flood and drought pressure, and At-Bay’s cyber claims data shows ransomware shifting toward infrastructure-led exploitation.
The actuarial theme is straightforward: capacity is abundant, but model risk is moving into the basis, correlation, and controls layers.
— Ron Richman, Founder, InsureAI
This Week’s Headlines
Aon: flood and drought are reshaping climate-risk portfolios
Aon’s 2026 Climate and Catastrophe Insight points to a familiar but increasingly awkward actuarial problem: the strongest signal is no longer just peak peril severity, but the accumulation of “ordinary” water stress events that break old geography assumptions. Aon estimates more than $42bn of global flood economic losses in 2025 and roughly $13bn from drought-related impacts.
Reinsurance NewsDecision Delta
- Signal: Flood and drought are moving from tail-event commentary into pricing, accumulation, and resilience assumptions.
- Functions affected: Property pricing, cat modelling, portfolio steering, reinsurance purchasing.
- Actuary action: Stress-test flood loadings and accumulation controls at a finer geographic resolution.
Zurich returns to cat bonds with $150m Turicum Re 2026-1
Zurich closed a $150m Rule 144A cat bond covering US named storms and earthquakes, its first natural catastrophe bond sponsorship since late 2012. The deal is per-occurrence, indemnity-triggered, and priced below guidance — a clean signal that investors still have appetite for well-managed peak peril portfolios when data quality and sponsor reputation are strong.
Reinsurance NewsDecision Delta
- Signal: Large carrier sponsors are using ILS capacity as strategic, multi-year reinsurance.
- Direction: More cedant optionality; continued spread compression for strong portfolios.
- Actuary action: Compare traditional reinsurance quotes with cat-bond economics for clean, modelled peak-peril layers.
Tower Hill upsizes Winston Re to $375m at lower pricing
Tower Hill secured $375m of fully-collateralised Florida named-storm protection through Winston Re 2026-1, a 67% increase from the initial $225m target. Artemis reports that each of the three tranches priced below initial guidance. Larger size plus lower pricing says a lot about current ILS demand for Florida wind when the structure and pricing stack are investable.
Artemis.bmDecision Delta
- Signal: ILS demand remains strong even in high-scrutiny Florida wind.
- Direction: Capacity abundant; cedants with credible exposure data have bargaining power.
- Actuary action: Revisit expected ceded cost assumptions and challenge stale hard-market loadings.
At-Bay: ransomware is shifting toward infrastructure-led exploitation
At-Bay’s 2026 InsurSec Report is a useful cyber-pricing warning. In its analysis of more than 6,500 claims and 100,000 policy years, 73% of ransomware incidents in 2025 began with VPN compromise; remote access tools were involved in 87% of ransomware claims; and average ransomware severity rose 16% to $508k.
Reinsurance NewsDecision Delta
- Signal: Ransomware frequency and severity are increasingly controlled by infrastructure posture.
- Direction: Higher segmentation value; blunt cyber relativities are becoming stale.
- Actuary action: Add explicit relativities for VPN exposure, remote-access tooling, MDR coverage, and vendor concentration.
From arXiv
Lead paper
Geography-driven MTPL frequency modelling
Revealing Geography-Driven Signals in Zone-Level Claim Frequency Models is the most actuarially useful paper in this week’s arXiv batch. Using the BeMTPL97 motor dataset, the authors ask a practical pricing question: when the geographic identifier is coarse, can external spatial features still improve motor third-party liability claim-frequency models?
The useful result is not “deep learning beats GLMs.” It is more actuarially grounded: coordinates and environmental features extracted at roughly 5km resolution improve both linear and tree-based models, while image embeddings add less once structured environmental variables are available. The lift comes from representing the underwriting object at the right spatial resolution, not from hiding geography inside a larger black box.
Read the paper →ActuBench
A multi-agent LLM pipeline for generating and evaluating actuarial reasoning tasks. Important less as a benchmark result than as evidence that actuarial reasoning is becoming a target domain for agentic evaluation.
Read on arXiv →Expectile-based parametric insurance
Optimises basis-risk weighting using expectiles. Useful for parametric cover design where mean error is too blunt and tail-sensitive mismatch matters.
Read on arXiv →Operational risk losses and macro regimes
Hidden Markov modelling of operational losses and macro variables. A good reminder that dependence assumptions should often be regime-conditioned, not fixed.
Read on arXiv →TabSHAP
Tabular explainability work worth bookmarking for pricing governance, feature attribution, and model-monitoring workflows.
Read on arXiv →From the Journals
Journal lead
Biological age for prevention in insurance
The strongest journal item this week is Biological age for prevention in insurance in the European Actuarial Journal. The paper compares biological-age methods — including regression, KDM, PhenoAge variants, and random forests — for mortality and disease-incidence prediction using NHANES data.
The actuarial interest is not just underwriting selection. Biological-age scores sit at the boundary between prediction, prevention, fairness, and customer actionability. If a score is used only to segment risk, it raises familiar anti-selection and discrimination questions. If it is used to support prevention and behaviour change, the modelling standard becomes higher: calibration, stability, explainability, and intervention response all matter.
Read the article →Offset vs ratio weighting in Tweedie models
A practical European Actuarial Journal paper on exposure treatment for mid-term cancellations. This is directly relevant to auto-pricing pipelines where earned exposure is not just a denominator.
Read the article →Auto insurance fraud detection
Journal of Risk and Insurance coverage of machine learning and deep learning for fraud detection. Useful as a governance and benchmark reference for claims analytics.
Read the article →Graph-based embeddings for categorical features
Highly relevant to actuarial tabular modelling: categorical levels are often relational objects, not arbitrary labels. This is one to connect to credibility, entity embeddings, and feature interaction design.
Read the article →Climate transition matrices
A firm-level carbon-performance transition framework. Relevant for climate-risk measurement, asset-side ESG modelling, and transition-risk scenarios.
Read the article →Practical Takeaways
Add more spatial diagnostics to flood, cyber, and motor frequency work; the risk signal is increasingly local and control-dependent.
Clean exposure data is valuable negotiating collateral in this ILS market; test cat-bond optionality before assuming traditional structures dominate.
Watch basis risk. Abundant capacity can hide model uncertainty.
VPN, remote access, and MDR variables should be treated as primary rating/control variables, not questionnaire clutter.
What We’re Watching
- Whether post-renewal cat-bond pricing continues to clear below guidance after the next meaningful US severe-convective-storm loss signal.
- How flood and drought loadings flow into primary property rates where regulatory approval cycles lag exposure change.
- Whether cyber insurers converge on infrastructure-led underwriting variables or keep relying on broad maturity scores.
- Whether geography-enriched public actuarial datasets become the next practical benchmark for explainable insurance ML.