The effectiveness of data science projects is one of the hottest topics in business intelligence nowadays. On the one hand, we are discussing the huge potential of artificial intelligence in executing sophisticated tasks for businesses. On the other hand, we see the harsh reality of today. Large companies like banking institutions are struggling hard to…
In the last five years of providing data science as a service to Europe’s largest banks, we have faced plenty of cases where banks were unprepared to work with their data. Unfortunately, this problem arises not only at the stage of creating a competency in the field of data science and…
Over the years, we have often heard from our clients that black box machine learning solutions are unacceptable. In the previous article, we went over three key questions to ask before using a black box model, and we proposed Bayesian networks as…
With the boost of computing power in past years, it has happened that almost anyone can run a sophisticated machine learning model, e.g. neural networks. And with modern frameworks such as Tensorflow, it is quite accessible and also popular to do everything with such a cool tool. But over the years, we have often heard…
Every company doing business in retail has been dealing with customer segmentation, and so have banking organizations trying to describe their client base effectively. Customer segmentation in banking is key to the success of marketing campaigns, product cross-selling and risk scoring. That’s why it’s critical for financial institutions to set up an efficient customer segmentation…