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With an eye on gaining a competitive edge in the marketplace, banks intend to drive customer engagement with data analytics. By analyzing their clients' economic activities, it is possible to detect patterns and behavior to offer personalized, tailor-made financial products to enhance customer satisfaction. However, the challenge lies in the banks' legacy systems, which can impede the ability to unlock the value of the data they already hold. In his talk, Marco presented a real-world example of predictive modeling in banking. He highlighted the used modeling practice and provided practical advice on the deployment process in a production banking environment. Additionally, Marco explored some best practice techniques on how to tackle data science projects.