Itua Etiobhio, Riyad Khan and Steve Blaxland
The volume of information available to supervisors from public sources has grown enormously over the past few years, including unstructured text data from traditional news outlets, news aggregators, and social media. This presents an opportunity to leverage the power of data science techniques to gain valuable insights. By utilising sophisticated analytical tools, can supervisors identify hidden patterns, detect emerging events and gauge public sentiment to better understand risks to the safety and soundness of banks and insurance firms? This article explores how data science could support central bank supervisors to discover significant events, capture public trends and ultimately enable more effective supervision.
