ACTUARIAL

CONSULTING

INSURANCE SUPERVISION UNDER SOLVENCY II

TASC provides qualitative and quantitative consulting on technical reserves and solvency position, addressing the requirements of supervisory authorities. Services include data validation, software development and implementation, sensitivity analysis, documentation, and, if necessary, communication with regulators. Leveraging expertise and prudential judgment, TASC offers consulting aligned with Solvency II standards.

CLIMATE CHANGE RISKS FOR INSURERS

With sustainability reporting becoming mandatory for many enterprises in 2023, the demand for climate change risk assessment has grown significantly. Climate risks are complex and have been extensively studied over the past decade. TASC supports companies by utilizing various climate change scenario platforms to evaluate these risks effectively.

Birds on a field, symbolizing the natural environment and biodiversity at risk due to climate change. TASC offers consulting services focused on assessing and addressing climate change risks.

INSURANCE

PRICING

Insurance pricing models vary depending on the type of risks, such as car accidents, life annuities, or flood damage, each requiring different methodologies. The availability of data is crucial for fair and competitive pricing and may influence the choice of statistical methods or models too. TASC aims at optimizing the use of available information and applying state-of-the-art analytical tools for precise and effective pricing solutions.

WITH EVA

Many insurers and reinsurers collect data on claims resulting from natural catastrophe (NatCat) events. This data provides a valuable source of information on the insurer’s specific exposure to such risks. Extreme Value Analysis (EVA) enables the estimation of key quantities such as return periods and return levels, exceedance probabilities, and other metrics relevant to NatCat pricing—even when only a relatively short historical record is available.

EVA is grounded in solid theoretical foundations, and many of its results do not rely on strict distributional assumptions, which helps avoid the risk of misspecification.

Compared to traditional NatCat models, EVA offers several advantages:

Lower modelling risk
Utilization of the insurer’s own claims data
More conservative (prudent) estimates
Transparency and explainability
Conceptual and computational simplicity

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