Peter Mitic
Santander UK
Peter Mitic says: I am Honorary Professor in the Department of Computer Science at University College London, and Head of Operational Risk Methodology at Santander Bank, UK. In the 1970s I studied mathematics at Oxford University, and later gained a PhD from the Open University, where I researched object-oriented modelling techniques with computer algebra. Following some years as a lecturer in mathematics, I have been working on risk-related projects in major banks in the UK and the Netherlands for more than twenty years. Most recently my main activities have been to develop new statistical techniques in operational risk, and to formulate a framework for measuring and investigating the statistical properties of reputational risk. During the past few years I have spoken at conferences numerous times, and have published papers and book chapters on risk-related topics. I am always looking for interesting things to investigate: you never know when they are going to turn up.
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Articles by Peter Mitic
Credible value-at-risk
This paper proposes a means to determine whether a a calculated VaR is "too large" and give a definition of this term within the context.
Correlations in operational risk stress testing: use and abuse
The paper presents an analysis of correlation effects of economic factors on the operational risk losses of a medium-large UK retail bank, and it recommends that causal factors that effect operational risk should be identified.
Incremental value-at-risk
This paper proposes a novel method for estimating future operational risk capital: incremental value-at-risk (IVaR)
Estimation of value-at-risk for conduct risk losses using pseudo-marginal Markov chain Monte Carlo
The authors propose a model for conduct risk losses, in which conduct risk losses are characterized by having a small number of extremely large losses (perhaps only one) with more numerous smaller losses.
A central limit theorem formulation for empirical bootstrap value-at-risk
In this paper, the importance of the empirical bootstrap (EB) in assessing minimal operational risk capital is discussed, and an alternative way of estimating minimal operational risk capital using a central limit theorem (CLT) formulation is presented.
Shapley allocation, diversification and services in operational risk
In this paper, the authors propose a method of allocating operational risk regulatory capital using a closed-form Shapley method, applicable to a large number of business units (BUs).
Reputation risk contagion
The aim of this paper is to assess the effects of the reputation of the members of a group on any single member of the group using the concepts of social influence and convergence in belief.