New Trends regarding the Operational Risks in Financial Sector

Risks, especially "operational risks" are part of corporate life, they are the essence of financial institutions' activities. Operational risks are complex and often interlinked and have to be managed properly. Today, there is more pressure to avoid operational risks while continuing to improve corporate performance in the new environment. The operational risk management of the future has to be seen in the wider context of globalization and Internet-related technologies. The two major future drivers - globalization and Internet-related technologies - will challenge the firms from financial sector to take on additional and partly new operational risk.operational risk, financial sector, models, trends

GeD spline estimation of multivariate Archimedean copulas

A new multivariate Archimedean copula estimation method is proposed in a non-parametric setting. The method uses the so called Geometrically Designed splines (GeD splines), recently introduced by Kaishev et al. (2006 a,b) [10] and [11], to represent the cdf of a random variable Wµ, obtained through the probability integral transform of an Archimedean copula with parameter µ. Sufficient conditions for the GeD spline estimator to posses the properties of the underlying theoretical cdf, K(µ; t), of Wµ, are given. The latter conditions allow for defining a three-step estimation procedure for solving the resulting non-linear regression problem with linear inequality constraints. In the proposed procedure,finding the number and location of the knots and the coefficients of the unconstrained GeD spline estimator and solving the constraint least-squares optimisation problem, are separated. Thus, the resulting spline estimator ^K (^µ; t) is used to recover the generator and the related Archimedean copula by solving an ordinary differential equation. The proposed method is truly multivariate, it brings about numerical efficiency and as a result can be applied with large volumes of data and for dimensions d ¸ 2, as illustrated by the numerical examples presented

Investigating the market potential for customised long term care insurance products

Previous economic research into long-term care (LTC) has mainly been focussed on one issue: the reasons why the LTC insurance market has not been successful. In this contribution, we analyse the prospects for a new type of insurance policy, which offers a top-up on the resources already available to the individual. We abstract from most problems inherent in LTC insurance markets and derive premium rates for various types of insurance policies. Generally, we find that the top-up option reduces premium rates considerably, to the point where it might be expected that a substantial number of people would take up policies, were they available

Tablas de mortalidad dinámicas con hoja de cálculo en la práctica actuarial

En este trabajo se presenta la aplicación de procedimientos de obtención de probabilidades de fallecimiento, mediante hoja de cálculo, para generaciones y años de calendario futuros, basadas en la información contenida en tablas de mortalidad dinámicas, desde el punto de vista actuarial

Enriching the statistics learning experience with D3.js interactive animations: Insurance applications of Markov chains

The aim of this paper is to explore the possibilities that online interactive animations offer to enhance the statistics learning experience in the field of actuarial education. A particular type of animation, based on the D3.js JavaScript library, has been chosen due to its powerful visualisation components and natural treatment of transitions. The latter is especially adequate for the graphical visualisation of Markov chains. Some insurance applications of discrete time Markov chains are simulated using this visual framework and used in a course of Stochastic Processes of the MSc in Actuarial Science at the University of Málaga. Finally, the results of the experience along with the outcomes of a survey conducted at the end of the course are analysed, revealing the main strengths of this approach perceived by the students. ------------------------------------------------------------------El objetivo de este artículo consiste en la exploración de las posibilidades que las animaciones interactivas pueden ofrecer para enriquecer la experiencia de aprendizaje de Estadística en el ámbito de la educación actuarial. Un tipo particular de animación, basado en la librería Javascript D3.js, ha sido seleccionado para ello por sus potentes componentes de visualización, así como por su tratamiento natural de las transiciones. Esta segunda característica es de vital importancia para la visualización gráfica de las cadenas de Markov. Algunas aplicaciones de las cadenas de Markov en el campo de los seguros se simulan usando este entorno y se han aplicado en el curso de procesos estocásticos del Máster en Ciencias Actuariales y Financieras de la Universidad de Málaga. Finalmente, se analizan los resultados de la experiencia, incluyendo los de una encuesta realizada al final del curso, que revelan las principales fortalezas del enfoque adoptado, tal como han sido percibidos por los estudiantes.  Artículo revisado por pare

The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee

The revised Basel Capital Accord requires banks to meet a capital requirement for operational risk as part of an overall risk-based capital framework. Three distinct options for calculating operational risk charges are proposed (Basic Approach, Standardised Approach, Advanced Measurement Approaches), reflecting increasing levels of risk sensitivity. Since 2001, the Risk Management Group of the Basel Committee has been performing specific surveys of banksÂ’ operational loss data, with the main purpose of obtaining information on the industryÂ’s operational risk experience, to be used for the refinement of the capital framework and for the calibration of the regulatory coefficients. The second loss data collection was launched in the summer of 2002: the 89 banks participating in the exercise provided the Group with more than 47,000 observations, grouped by eight standardised Business Lines and seven Event Types. A summary of the data collected, which focuses on the description of the range of individualgross loss amounts and of the distribution of the banksÂ’ losses across the business lines/event types, was returned to the industry in March 2003. The objective of this paper is to move forward with respect to that document, by illustrating the methodologies and the outcomes of the inferential analysis carried out on the data collected through 2002. To this end, after pooling the individual banksÂ’ losses according to a Business Line criterion, the operational riskiness of each Business Line data set is explored using empirical and statistical tools. The work aims, first of all, to compare the sensitivity of conventional actuarial distributions and models stemming from the Extreme Value Theory in representing the highest percentiles of the data sets: the exercise shows that the extreme value model, in its Peaks Over Threshold representation, explains the behaviour of the operational risk data in the tail area well. Then, measures of severity and frequency of the large losses are gained and, by a proper combination of these estimates, a bottom-up operational risk capital figure is computed for each Business Line. Finally, for each Business Line and in the eight Business Lines as a whole, the contributions of the expected losses to the capital figures are evaluated and the relationships between the capital charges and the corresponding average level of Gross Incomes are determined and compared with the current coefficients envisaged in the simplified approaches of the regulatory framework.operational risk, heavy tails, conventional inference, Extreme Value Theory, Peaks Over Threshold, median shortfall, Point Process of exceedances, capital charge, Business Line, Gross Income, regulatory coefficients

Still living with mortality: The longevity risk transfer market after one decade

This paper updates Living with Mortality published in 2006. It describes how the longevity risk transfer market has developed over the intervening period, and, in particular, how insurance-based solutions – buy-outs, buy-ins and longevity insurance – have triumphed over capital markets solutions that were expected to dominate at the time. Some capital markets solutions – longevity-spread bonds, longevity swaps, q-forwards, and tail-risk protection – have come to market, but the volume of business has been disappointingly low. The reason for this is that when market participants compare the index-based solutions of the capital markets with the customized solutions of insurance companies in terms of basis risk, credit risk, regulatory capital, collateral, and liquidity, the former perform on balance less favourably despite a lower potential cost.We discuss the importance of stochastic mortality models for forecasting future longevity and examine some applications of these models, e.g., determining the longevity risk premiumand estimating regulatory capital relief. The longevity risk transfer market is now beginning to recognize that there is insufficient capacity in the insurance and reinsurance industries to deal fully with demand and new solutions for attracting capital markets investors are now being examined – such as longevity-linked securities and reinsurance sidecars

Statistics Department 2013 Newsletter

https://digitalcommons.calpoly.edu/stat_news/1008/thumbnail.jp

AS-937-22 Resolution on New Degree Program for Masters of Science in Statistics

Approves the new degree program for final review by the Chancellor’s Office