Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.
For a while, we have been running a blog series on cognitive biases and logical fallacies that data scientists should avoid. In philosophy there are a host of informal logical fallacies – essentially errors in thinking – that crop up every day. In this series we have looked at the practice of data science to determine how these same fallacies also occur. Today we will be looking at fallacies and their manifestation in credit: The Monte-Carlo fallacy and the Hot-hand fallacy with some studies in the credit world.
As part of the group that was the second company worldwide to become IFRS9 compliant, IFRS9 has been at the forefront of what we do. We have assisted nearly 20 companies on their IFRS9 journey over the last two years. This blog forms part of a more extensive series on IFRS9. In this blog, we explore the administering of management overrides.
The Simpson's Paradox is a phenomenon in statistics illustrating how easy it is to misinterpret data. (Click to Tweet!) It occurs mainly in descriptive and diagnostic analytics (see our blog on the different types of analytics) where an analyst may jump to a conclusion driven by motivated reasoning and not by objectively assessing the evidence.
As part of our blog series on cognitive biases and logical fallacies that data scientists should avoid, today we address a prevalent logical fallacy: the "correlation proves causation" fallacy. Correlation due to causation is just one of the five main categories of causation, and this blog will look into each of the five.