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Insurance Mathematics and Economics
Article . 2011 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
SSRN Electronic Journal
Article . 2010 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2010
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Impact of insurance for operational risk: Is it worthwhile to insure or be insured for severe losses?

Authors: Pavel V. Shevchenko; Gareth W. Peters; Gareth W. Peters; Aaron D. Byrnes;

Impact of insurance for operational risk: Is it worthwhile to insure or be insured for severe losses?

Abstract

Under the Basel II standards, the Operational Risk (OpRisk) advanced measurement approach allows a provision for reduction of capital as a result of insurance mitigation of up to 20%. This paper studies the behaviour of different insurance policies in the context of capital reduction for a range of possible extreme loss models and insurance policy scenarios in a multi-period, multiple risk settings. A Loss Distributional Approach (LDA) for modelling of the annual loss process, involving homogeneous compound Poisson processes for the annual losses, with heavy tailed severity models comprised of alpha-stable severities is considered. There has been little analysis of such models to date and it is believed, insurance models will play more of a role in OpRisk mitigation and capital reduction in future. The first question of interest is when would it be equitable for a bank or financial institution to purchase insurance for heavy tailed OpRisk losses under different insurance policy scenarios? The second question then pertains to Solvency II and addresses what the insurers capital would be for such operational risk scenarios under different policy offerings. In addition we consider the insurers perspective with respect to fair premium as a percentage above the expected annual claim for each insurance policy. The intention being to address questions related to VaR reduction under Basel II, SCR under Solvency II and fair insurance premiums in OpRisk for different extreme loss scenarios. In the process we provide closed form solutions for the distribution of loss process and claims process in an LDA structure as well as closed form analytic solutions for the Expected Shortfall, SCR and MCR under Basel II and Solvency II. We also provide closed form analytic solutions for the annual loss distribution of multiple risks including insurance mitigation.

Keywords

FOS: Computer and information sciences, Statistical Finance (q-fin.ST), Quantitative Finance - Statistical Finance, Statistics - Applications, Statistics - Computation, Methodology (stat.ME), FOS: Economics and business, Risk Management (q-fin.RM), Applications (stat.AP), Statistics - Methodology, Computation (stat.CO), Quantitative Finance - Risk Management

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    18
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Average
Top 10%
Top 10%
Green
bronze