Does Lost Time Cost You Money and Create High Risk?

The aim of the case study is to express the delayed repair time impact on the revenues and profit in numbers with the example of the outage of power plant units. Main steps of risk assessment: • creating project plan suitable for risk assessment • identification of the risk factors for each project activities • scenario-analysis based evaluation of risk factors • selection of the critical risk factors based on the results of quantitative risk analysis • formulating risk response actions for the critical risks • running Monte-Carlo simulation [1] using the results of scenario-analysis • building up a macro which creates the connection among the results of the risk assessment, the production plan and the business plan.

Analysis of operational risk of banks – catastrophe modelling

Nowadays financial institutions due to regulation and internal motivations care more intensively on their risks. Besides previously dominating market and credit risk new trend is to handle operational risk systematically. Operational risk is the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. First we show the basic features of operational risk and its modelling and regulatory approaches, and after we will analyse operational risk in an own developed simulation model framework. Our approach is based on the analysis of latent risk process instead of manifest risk process, which widely popular in risk literature. In our model the latent risk process is a stochastic risk process, so called Ornstein- Uhlenbeck process, which is a mean reversion process. In the model framework we define catastrophe as breach of a critical barrier by the process. We analyse the distributions of catastrophe frequency, severity and first time to hit, not only for single process, but for dual process as well. Based on our first results we could not falsify the Poisson feature of frequency, and long tail feature of severity. Distribution of “first time to hit” requires more sophisticated analysis. At the end of paper we examine advantages of simulation based forecasting, and finally we concluding with the possible, further research directions to be done in the future.