Prediktívna analytika v retailovom bankovníctve v Českej republike

Advanced analytics and big data allow a more complete picture of customers' preferences and demands. Through this deeper understanding, organizations of all types are finding new ways to engage with existing or potential customers. Research shows that companies using big data and advanced analytics in their operations have productivity and profitability rates that are 5 to 6 percent higher compared to their peers. At the same time it is almost impossible to find a banking institution in the Czech Republic exploiting potential of data analytics to its full extent. This thesis will therefore focus on exploring opportunities for banks applicable in the local context, taking into account technological and financial limitations as well as the market situation. Author will conduct interviews with bank managers and management consultants familiar with the topic in order to evaluate theoretical concepts and the best practices from around the world from the point of Czech market environment, to assess capability of local banks to exploit them and identify the main obstacles that stand in the way. Based on that a general framework for bank managers, who would like to use advanced analytics, will be proposed.