. about two years ago, most of our countries concluded the second phase of the general data dissemination system ( gdds ) project which was aimed at improving the availability and quality of data, in developing countries. this was important in order to conform to international standards. some of the major achievements of the monetary module of this project include the correct classification of key financial assets and liabilities and sectorization of transactions for the main deposit taking institutions in our financial sectors. the end result was the compilation and filing of standard reports by most of the eac countries with the imf statistics department. bis central bankers ’ speeches again i recall that towards the end of last year, the imf approached most of our countries to consider joining the enhanced data dissemination initiative ( eddi ). the focus of the eddi is to consolidate the gains realized under the gdds while expanding the institutional coverage in statistical compilation to include other deposit taking institutions such as saccos and microfinance ; and other key financial sector institutions such as pension funds and insurance companies. i am aware that the work plans were prepared during the first eddi workshop in kampala and the imf has identified technical experts for each of our countries. this workshop is therefore part of the greater plan towards the improvement of statistics in the region by the imf. i wish to sincerely thank the imf for these initiatives. it is only appropriate at this juncture to recognize, ladies and gentlemen, the critical role that the eac secretariat has played in providing an elaborate roadmap on how statistical harmonization can be achieved within the eac region. however, for this to succeed, an appropriate mechanism, in terms of institutional arrangements and legal frameworks, has to be put in place to guard and guide the production of harmonized and quality statistics in the eac partner states and more importantly, at the regional level. these statistics will inform policy formulation and implementation in the integration process. all countries have their own data collection, storage and processing centres. it is a question of how we can pick the important aspects from our own areas for use, standardization and centralization. ladies and gentlemen, in concluding my remarks, i welcome you once again to kenya and to this workshop. though the duration of the workshop is short, please find time to visit some of our beautiful sceneries around town and sample what the city of nairobi has to offer. it is now my pleasure and humble duty to declare this workshop officially open. thank you. bis central bankers ’

institution ’ s return objectives and views toward risk. as you all know, most progress has been made in the measurement of market risk and much work is now being done in many places to construct models for a better management of credit risk. difficulties with credit risk measurement lies in the lack of statistics about individual default probabilities. even if these default probabilities can be estimated reasonably accurately, it is still rather difficult to combine them into portfolio assessments. the reason for that partly stems from the lack of statistical knowledge about the interaction between variables. therefore, the models mostly tend to rest on simplified assumptions based on subjective judgments. i do not want to go into details about the technical aspects of the risk measurement methods, but i would like to emphasize that it is necessary to combine them with sound judgment and common sense. since these models are no more than simplified and limited images of the real world, they are better to be used having this fact in mind and the decisions must be taken not solely relying on the results of these models. the results should be supported with scenario analysis, stress testing and most importantly with the sound judgment of the decision makers. another important aspect of risk analysis is that it should be integrated, meaning that the analysis results for different risk types should be comparable with each other to facilitate decision making. it necessitates that the assumptions, data, valuation models used in analyzing different types of risks be the same or at least consistent with each other. organizationally, the integration of risk analysis requires that there be a single, common risk management authority for the whole organization. at the beginning, it might not be easy to look at risk on an institution wide basis. since it requires a considerable amount of capital to be invested either in terms of technology, or in terms of staff. besides that, the risk management system must be flexible enough to adjust to the rapid developments in this area. so, at the end, the risk management system should be established in a way to allow the management to compare risk on a consistent “ apples for apples ” basis even for those risk factors such as operational and legal risk, where limited data is available. as i mentioned earlier, the management not only has to set standards for its risk policies but also has to ensure that they are disseminated to and understood by the staff who are affected by them. i think this point is worth restressing since it is impossible to launch the risk culture without ensuring those kind of communication channels in the organization. at this