Big Data and Machine Learning Won’t Save Us from Another Financial Crisis

Ten years on from the financial crisis, stock markets are regularly reaching new highs and volatility levels new lows. The financial industry has enthusiastically and profitably embraced big data and computational algorithms, emboldened by the many triumphs of machine learning. However, it is imperative we question the confidence placed in the new generation of quantitative models. Two areas are of particular concern. First, there are many unsettling parallels between the recent advances in machine learning and algorithmic trading and the explosive growth of financial engineering prior to the crisis. Secondly, we cannot draw comfort simply from more data and greater computing power: statistical theory shows that big data does not necessarily prevent big trouble.