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Friday 05 November 2010
Author: Russell Group

Reinsurance intermediary Aon Benfield has criticised the planned calculations for natural catastrophes under the solvency II regime as a step backwards.

The firm said the proposed natural catastrophe calculations are “ignoring 15 years of critical evolution” under the currently proposed Solvency II Standard Formula, warning it could lead to higher capital requirements for insurers when the regulation comes into force.

Paul Miller, head of international catastrophe management at Aon Benfield, said: “The proposed Standard Formula for catastrophe is a disappointing backward step in catastrophe modelling. For the majority, the standard approach will be inappropriate or give unreasonable results as data quality and portfolio differentiators are totally ignored. The next two years are crucial for brokers to provide catastrophe modelling support as re/insurers register internal models with the regulator and demonstrate how they are using advances in catastrophe modelling to obtain a more realistic picture of their risks.”

The intermediary added: “Catastrophe risk is a key driver for capital under Solvency II, with the benchmark to withstand a 1-in-200 year event for natural and man-made disasters. There is a basic calculation method that insurers can use to determine their Solvency Capital Requirement.”

However it said the methodology for the standardized scenarios for natural catastrophe modelling overlooks key data features including:

  • Location granularity (CRESTA zone data is insufficient)
  • No differentiation by occupancy (residential, commercial or industrial) or construction, age and height
  • Single damage function so no differentiation between buildings, contents and business interruption cover
  • No application of limits and deductibles

“The use of CRESTA zone data in exposure calculations was common 15 years ago, but now most re/insurers (and all commercial catastrophe models) utilize far more detailed data,” added Mr Miller. “This means re/insurers could be relying on inaccurate data to establish their risk, resulting in higher capital requirements. “