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Authors propose a new process-event approach for quantitative estimation of operational risk in a bank and calculation the amount of economic capital in dynamics. The proposed approach, according to the Basel II Capital Accord, belongs to the category of “advanced methods”. Operational risk is not financial risk and appeared in unfavorable events mainly. A number of business processes are performed in banking activity. Every business process contains a set of routines (operations), which can be interrupted by operational risk events with certain losses. The main idea of the approach is to describe processes as chains of casual events instead of a traditional graphic description as diagrams. Authors introduce new concepts: an elementary process event, a chain of process events, a time diagram of enterprise’s event flow, and build logical and probabilistic risk models. Methods and formulas for calculation the current and integrated operational risk in dynamics, the amount of economic capital, upper and lower limits of reservation, are given. The value of integrated operational risk can be used as a rating of the current reliability of the bank. The paper outlines the advantages and disadvantages of proposed process-event approach. Research results can be implemented as analytical tool in risk management technology, “process mining” technology and in bank intelligent management systems. 

The evidence theory is ascribed to a specific kind of uncertainty. In this theory, uncertainty refers to the fact that the element of our interest (the true world) may be included in subsets of other similar elements (possible worlds). In the original evidence theory, the estimates of the basic probability masses for the focal elements are given in an unambiguous form. In practice, to obtain such estimates is often difficult or even impossible. In such a situation, the relevant estimates are given in the interval or fuzzy form. The goal of the paper is to present and analyse the calculation procedures for determination of the belief functions and plausibility functions in the evidence theory for cases when the initial estimates are given in the interval or fuzzy form.

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