In March 2020, we published a paper touching upon the importance of data analytics during times of high market volatility. Since then, the global pandemic resulted in an economic crisis, followed by the quickest market rebound in our history. Over the last months, developments have gone fast and the world is currently facing a second ‘wave’ of infections, which triggers new restrictions and economic consequences. To reflect on the effects of the COVID-19 pandemic in the March issue, two industry focused cases on bankruptcy of hard-hit, listed businesses were presented. These volatile times are forcing professionals to be on top of the potential emerging risks even more in order to tackle them efficiently. 

This paper reflects on the events that happened in 2020, and how Natural Language Processing (NLP) and Machine Learning helps being on top of an emerging risk for one party, while creating investment opportunities for others. 

In short, it shows;

• how the application of NLP helps with both risk mitigation and origination of business opportunities and how these can go hand in hand;
• how our risk-based scoring models flag emerging risk and are able to identify specific events relevant to risk, portfolio and asset managers;
• how the exploration of diverse and global news and data sources provide early insights, which are often not directly covered by mainstream media;
• how current times make the adoption of new technology mandatory to stay ahead of the market or prevent from going down with it.

Companies that excel in navigating through high market volatility are able to respond quickly to new available information. Having swift access to the right information and the competence and tooling to work with the data is key in every sector, whether that is how we adapt our healthcare systems, restructure business operations or supply chain. Next to this, it allows for  choosing alternative approaches to how we manage risk and create alpha going forward – which, in these unprecedented times, has become more important than ever.

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