On 11 July 2018, the FCA published a speech given by its chairman, Charles Randell in which he discusses Big Data.

The focus of Mr Randell’s speech is how technological advances may draw society towards an algocracy, rather than a democracy – where decisions are decided by algorithms. Three factors could facilitate this:

  • Big Data: the ability to store data cheaply has created enormous and detailed datasets about different aspects of our lives;
  • Artificial intelligence and machine learning: improvements in processing power means corporations can mine Big Data sets for patters more effectively than before. Patterns can draw conclusions and make predictions about us as individuals; and
  • Behavioural science: firms may be able to target their sales using ‘nudges’ informed by the Big Data they hold.

Considering the impact of an algocracy, the FCA has recognised that consumers should take responsibility for their decisions.  Consequently the regulator has incorporated ‘behavioural science’ within its regulatory toolkit. Further consideration needs to be given to how to mitigate the particular risk that algocracy exacerbates social exclusion and worsens access to financial services by identifying the most profitable or risky customers.

Three elements are considered to form the foundation of good innovation in relation to Big Data and an algocracy – purpose, people and trust.

  • Purpose: The FCA has identified a firm’s purpose as driving the firm’s culture. The availability and use of very personal data may call the purpose of many existing business models into question.
  • People: People must be held accountable for innovation through sound systems of risk management, governance and control. Moreover, technology needs to be implemented with human judgement in all aspects, ensuring the outcomes that the technology produces delivers ethically acceptable results.
  • Trust: Firms need to be part of the communities they serve so as to understand society’s views on personal data. Trust requires good communication with consumers so that consumers understand a firms approach to using their data.