Risk assessment - for example Value at Risk (VaR) - affects different key indicators, depending on the sphere of risk (market risk, counterparty risk, operational risk oder system risk). From this result typical Big Data topics: Systems, which calculate and report such risk key figures have to deal with large amounts of data (volume) and must use current market and trade data that change continuously (velocity). The data have to be analysed and grouped on basis of different aspects to produce the right reports.
Advantages of our Big Data approach:
Real-time data, decisions and customer feedback
Predictive models for forecasts including validation (back and forward testing)
Dashboards and reporting for result processing
Generating of as many scenarios as possible while using mathematical algorithms (Monte Carlo Simulation)
Assessment of trades or businesses , for example with Black and Scholes Model for prices of transactions (trades)
Aggregation of risk exposition of single trades on several hierarchy level (portfolio, netting set)
Reporting of results, for different stakeholders, according to variable criteria
Our experts support you to choose the right Big Data scenario.