Project goal: To determine which technique performs best when combining internal loss data and scenario loss datafor purposes of estimating operational risk capital in a LDA model.

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Project goal: To determine if quantitative techniques can be used to perform Macro-Economic Stress testing inrespect of Operational Risk, for example whether there exists a causal link between macroeconomicfactors and operational losses that can be used to construct a model.

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Project goal: To develop a model to assist banks to optimally meet the Basel III minimum capital and liquidityrequirements and highlighting possible constraints or areas of concern the banks may face.

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Project goal: To enable CIB Portfolio Management to accurately value, price and enhance strategic decision makingon loans by constructing accurate credit curves.

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Project goal: To determine which statistical distributions, if any, can be used as an alternative to splice distributionsfor modelling the severities in operational risk quantification.

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Project goal: To gain insight into the pricing and hedging of minimum rate of returnguarantees (MRRG) embedded in participating (or profit-sharing) life insurance policies.

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Project goal: To compare different techniques for approximating the quantiles of compound distributions in terms oftheir practical usefulness.

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Project goal: To use the pooled credit data like the Global Credit Data (GCD) (formerly known as the Pan-EuropeanCredit Data Consortium (PECDC)) during the development of new models in corporate loss givendefault (LGD) modelling.

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Project goal: To propose new methodologies (and compare existing methodologies) in thepredictive modelling context.

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Project goal: To propose a semi-supervised segmentation method and to do empiricalstudies on the performance of this method.

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Project goal: To develop a multi-period optimisation model for a credit portfolio in Business Banking.

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Project goal: To answer the question, "what is an efficient, practical method for pricing and risk-managing derivatives – and portfolioscontaining derivatives – in dynamic markets?"

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