An Inter-disciplinary Approach to Automation Technology in Finance - What Can History, Law and Data Science Teach Us?

The year 2008 is etched in human history as the year of the ‘Global Financial Crises’. Post the crises, Historians and financial commentators alike rushed to impute blame. Some blamed securitizations, some the banks and some Lehman Brothers and AIG. However, in the midst of all of this humbug, a key epicentre of the crises escaped academic scrutiny; ‘Automation Technology’. The paper therefore aims to present an alternative view of financial history; one which impleads ‘automation technology in finance’ i.e., Risk Modelling Algorithms and RegTech. However, the underlying aim of this paper is to make a case against systemic automation bias in finance and to achieve that end, the paper employs an inter-disciplinary approach and uses history, law and data science to show case the multifarious perils of using automation technology blindfold in finance whilst also proposing possible solutions such as the incorporating of design thinking and systems theory in finance. Expired data sets, human assumptions, turning code in law, and a lack of standardized financial semantics as but some of these ‘perils’. On the law front; it presents a twofold challenge under constitutional and anti-trust law and aims to reconcile law and technology. Lastly the paper aims to guide regulators by categorizing multiple stages of technological complexity and recommends application of different regulatory approaches to regulating automation. Therefore, the paper shall maintain a ‘solution’ oriented approach throughout.