Operational risk capital and insurance in emerging markets

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Table 5: Parameters of possible configurations insurance schemesThe convolution procedure to obtain aggregate losses now takes into account theformula (5) introduced in the previous section. The procedure follows these steps1. Define the values for the parameters of the insurance agreement (either A or B)2. Generate n from the Poisson function (bad control situation)3. Generate n losses z of the Log-Normal distribution (low-risk situation)4. Estimate S seg according to equation (5)5. Return to step 2 and repeat NSim (100 000) times6. Obtain the expected values and a-percentiles of generated distribution F seg(S) .7. Estimate the implied operational risk capital with ORC fa = F _ 1seg (a) _ E(S seg ) .Table 6 summarizes the results. In the “favorable” insurance scheme (A), the 99,9percentile is reduced by US$ 212 thousand whereas the value of the expectedmean loss falls by US$ 52 thousands. This means that the operational risk capitalreduction is about US$ 160 thousands. On the other hand, under insurance B, thedifferences between the ex-ante and ex-post insurance cases are not very distinct.Under this scheme the operational risk capital falls only by US$ 16 thousands. Inpractice, these small effects are not significant enough 22 .Table 6: Operational risk capital before and after the insurance22 In some situations this may imply that the effect of insurance might be lower than its costsSBS Revista de Temas Financieros 46
As a conclusion, the introduction of insurance in operational risk capital estimationmay have different results depending on i) the conditioning factors and environmentsurrounding financial institutions and ii) the particular insurance schemes taken bythese institutions. The proposed methodology has precisely provided a useful toolto assess the relative benefits of the aforementioned factors.IV. CONCLUSIONSThis paper emphasizes the importance of insurance in the estimation of operationalrisk capital and the management of operational risk. Four features of insurance havebeen highlighted as key to operational risk: its loss-financing role, its promotion ofbest risk management practices, its potential to supply a rich operational risk datasource and its role as a provider of analytical methods to estimate operational riskcapital.Operational risk capital charges might turn out expensive because operationalrisks have the nature of being pure risks which give no return to its bearer. So,operational risk insurance covering unexpected losses become a good alternativeto operational risk capital.Insurance on the other hand, also functions as a catalyst of good practices inoperational risk management and internal control. The insurance and reinsurancebusinesses are guided by standardized principles that require - financial institutionsthat take insurance - not only the timely premium payments; but also, the fulfillmentof specific commitments regarding sound risk management practices.This paper proposes the use of information that the international insurance industryhave collected over decades. The advantages of these data source are consideredto be beneficial for financial institutions, insurers and regulators. This is essential inemerging markets because many of their financial regulators will freely adopt Basel2 guidelines in the future and will accept the use of AMA; and unlike developedeconomies, these countries do not have access to comprehensive and systematicexternal data sources. So regulators in these countries might find beneficial topromote the existence of an international data center based on the yet unexploitedinsurance system data.In the second part of the paper, a comprehensive LDA estimation is carried outin order to compare the effects of insurance under different schemes. A keySBS Revista de Temas Financieros 47
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