Tag: data science

Measuring of Competition Using Natural Language Processing

Written by Rashid Muhamedrahimov and Ethan Soo Summary As the competition landscape is constantly evolving, the question still remains: Is there a need to revamp the way we measure closeness of competition? There are many standardised ways to measure how close competitors are. We can supplement these measures with evidence that has traditionally been difficult … Continued

Providing New Evidence: Using AI in Merger Proceedings

Written by Enrico Alemani and Jaime Coronado Natural language processing (“NLP”) is a branch of Artificial Intelligence (“AI”) focused on how computers can understand language (e.g. written text) in much the same way human beings do. In this article, the data science team explores how NLP can be a new helpful tool in merger proceedings, … Continued

Data Visualisation: Crossing the line

Written by Tristan Salmon and James Forster In this article, the data science team illustrate intuitive ways to explore and visualise complex data using the example of the how, where, when and who of the COVID-19 pandemic. Traditional charts (and in particular, line charts) are very popular in economic consulting. At their best, they present … Continued

Game, Set and Fuzzy match

Written by Bhargav Bharadwaj, Antoine Gracia Victoria, Wiktor Owczarz and Waldemar Schuppli Fuzzy matching is a set of data science techniques that save critical time and reduce the risk of human error when matching string variables (e.g., customer names) in large, distinct datasets, for example, to assess the closeness of competition between merging firms, or … Continued