The topic of ethical implications of the exploding applications of big data, machine learning and genuine AI has quickly captured the attention of industry practitioners, public observers like journalists, politicians and definitely conference organisers over the past year. It is a vast topic in its own right, deserving all the multidisciplinary attention it gets. In this short commentary, I will limit myself to reviewing some salient features of bias in the context of models used in the financial industry, and, more importantly for the practitioner, suggest some process and governance measures that boards and senior management of financial services companies can take to identify, monitor and mitigate this risk exposure.
The world’s most valuable resource is no longer oil, but data. (Economist.com – May 6th, 2017). Data is the new gold. Data is going to be the most important asset in the future. And many other statements like these are popping up continuously as people are discovering the potential of big data.