QMetrics aims to support organizations that are facing complex challenges by providing new context-relevant insights to guide decisions. These insights will be obtained from available data through the application of advanced econometric models. Overall, the goal of QMetrics is to provide information that can really make a difference in organisational outputs and achievements. In general, econometric models may be classified into forecasting or optimization models and the solutions QMetrics provides take both kinds of models into consideration. For example, forecasting models include both time-series models (ARIMA, GARCH – models) and models for cross-sectional data whereas optimization models include clustering and decision models. Examples: • How to cluster your customer base to adapt your products/services and (E)–marketing in an optimal way? • How to construct an optimal asset hedge portfolio to reduce the market- and insurance risk resulting from the liabilities towards the policy holder? (ALM) • What is the optimal price formula that a telephone company can use given the data about the call behaviour of their customers? • How to predict the probability of default of your customers to avoid default and fraud based on the payment history of the customers? • How to predict what type of customers will buy what kind of products given data about your customers and products? • How can the purchasing habits of your online customers be predicted using their online behavior? • How can regional car sales be predicted using data such as macro-economic variables, sales of competitors, seasonal effects, fiscal regime etc.? QMetrics possesses the capacity required to answer all of the questions above. The above-mentioned complex cases are present in every industry. However, each industry has its own dynamics and characteristics. Therefore, the solutions provided by QMetrics are tailor-made. Interested, contact me at info@qmetrics.be/mienvu.dang@qmetrics.be