Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.
For businesses wishing to improve their credit decisions, the adoption of Mathematical Optimisation is an important consideration. Mathematical optimisation is more than a straight data-driven strategy design as it incorporates prescriptive analytics.
We have released a new eBook titled Truth Seeker: a guide to avoiding logical fallacies and cognitive biases in data science.
We’re looking forward to attending this year’s Evolution of Data Science in Banking conference. The 2019 conference will be held on the 5th and 6th of June at the Indaba Hotel, Fourways, Johannesburg. The event will explore the use of data and analytical techniques to help financial services providers meet regulatory and reporting requirements. Also to be discussed is how running analytics at a product level can provide a more holistic view of customers across their portfolios.
For a while, we have been running a blog series on cognitive biases and logical fallacies that data scientists should avoid. In this final blog on the subject, we look at some of the other logical fallacies and how they might crop up in data analytics.
With LinkedIn usage growing by two new members every second, you simply can’t afford to not be on the platform. Founded in 2003, LinkedIn has 590 million users with 260 million of those active every month.