A European Deposit Insurance and Resolution Fund - An Update. CEPS Policy Brief No. 283, 11 September 2012

Cross-border banking is currently not stable in Europe. Cross-border banks need a European safety net. Moreover, a truly integrated European level banking system may help to break the diabolical loop between the solvency of the domestic banking system and the fiscal standing of the national sovereign. This policy paper first sketches the building blocks of a banking union. Importantly, a new European Deposit Insurance and Resolution Authority (EDIRA) should start simultaneously with the ECB assuming supervisory powers. A combination of European supervision and local resolution cannot work because it is not ‘incentive compatible’. Next, this paper proposes a transition period to gradually phase in the European deposit insurance coverage. Finally, we calculate that a European Deposit Insurance Fund would amount to about €30-50 billion for the 75 euro area banks that were subject to the EBA stress tests. This Fund could be created over a period of time through risk-based deposit insurance premiums levied on these banks. Once up and running, the Fund would then turn into a European Deposit Insurance and Resolution Fund to also deal with the resolution of one or more of these European banks.

Risk pricing practices in finance, insurance and construction

A review of current risk pricing practices in the financial, insurance and construction sectors is conducted through a comprehensive literature review. The purpose was to inform a study on risk and price in the tendering processes of contractors: specifically, how contractors take account of risk when they are calculating their bids for construction work. The reference to mainstream literature was in view of construction management research as a field of application rather than a fundamental academic discipline. Analytical models are used for risk pricing in the financial sector. Certain mathematical laws and principles of insurance are used to price risk in the insurance sector. construction contractors and practitioners are described to traditionally price allowances for project risk using mechanisms such as intuition and experience. Project risk analysis models have proliferated in recent years. However, they are rarely used because of problems practitioners face when confronted with them. A discussion of practices across the three sectors shows that the construction industry does not approach risk according to the sophisticated mechanisms of the two other sectors. This is not a poor situation in itself. However, knowledge transfer from finance and insurance can help construction practitioners. But also, formal risk models for contractors should be informed by the commercial exigencies and unique characteristics of the construction sector.

Towards the "cult of the equity"? Insurance companies and the interwar capital market

This article examines the ways in which insurance companies modified their investment policies during the interwar years, arguing that this period marked the start of the transition from ‘traditional’ to ‘modern’ investment practice. Economic and financial conditions raised considerable doubts regarding the suitability of traditional insurance investments, while competitive conditions forced insurance offices to seek higher-yielding assets. These pressures led to a considerable increase in the proportion of new investment devoted to corporate securities, including ordinary shares. Meanwhile new insurance investment philosophies began to be advocated, which accorded both legitimacy and importance to the role of ordinary shares in insurance portfolios.

The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed.

Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.