![]() The Berka Dataset, or the PKDD’99 Financial Dataset, is a collection of real anonymized financial information from a Czech bank, used for PKDD’99 Discovery Challenge. Fortunately, there is an exception: the Berka Dataset. In other words, there are not many real-world datasets that we can use if we want to work on such financial projects. The datasets used by them are most likely to be proprietary and are usually collected internally through their daily businesses. In the modern era, the data science teams in the banks build predictive models using machine learning. Introductionįor banks, it is always an interesting and challenging problem to predict how likely a client is going to default the loan when they only have a handful of information. If you are interested in this topic and want to see some more in-depth work that I accomplished for a client, using optimization to turn their loss into profit using such loan default prediction models, please see my other article here: Loan Default Prediction for Profit Maximization. This post is just a hands-on practice building a loan default prediction model. Note: If you are interested in the details beyond this post, the Berka Dataset, all the code, and notebooks can be found on my GitHub Page. Photo by Sean Pollock on Unsplash Table of Content ![]()
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