ANZ is using machine learning to improve the accuracy of data forecasting

ANZ Bank has turned to machine learning to improve existing forecasting techniques. Economists Jack Chambers and David Plank applied the technique to monthly retail sales data, and compared it to the standard error found in consensus surveys compiled by Bloomberg. The machine learning process used by the pair was called "random forest". Think of a standard decision tree model, which maps out decisions or actions and their possible consequences. It follows that the "forest" is comprised of multiple decision trees, which are calculated and averaged to find correlations with retail sales.