Knowledge graphs have emerged as a compelling abstraction for organizing world’s structured knowledge over the internet, capturing relationships among key entities of interest to enterprises, and a way to integrate information extracted from multiple data sources. Knowledge graphs have also started to play a central role in machine learning and natural language processing as a… Read more »
The purpose of this paper is to show a novel approach to automatically generating Probabilistic Causal Models (Bayesian Networks (BN)) by applying Natural Language Processing (NLP) techniques to a corpus of millions of digitally published news articles in which views by different authors are expressed on the future states of economic and financial variables, and… Read more »
Causality Link co-founder and CTO Eric Jensen joins Quantiphi and Amazon Web Services (AWS) in a webinar on how fintech startups can leverage seamless document processing, custom ML models and AI-powered virtual assistants to solve business problems. In this webinar, Eric shares how our technology collects millions of documents globally, reading more than 50,000 articles… Read more »
On June 24, 2019 at The Economic Club in Washington, D.C., Bill Gates was asked: “If you were 20 years old today and you wanted to start a new company, drop out of Harvard, what area would you want to start it in?” He responded: “Given my background, I would start an AI company whose… Read more »
In this paper, we describe the growing risk of a second COVID shock due to the increased probability of the emergence of an escape variant of the virus. Using causal links learned from the first shock, we analyze the way the market reacted over time to the pandemic, and the differential impact of a second… Read more »
In May 2020, Causality Link co-founder and CEO, Pierre Haren, joined leaders in technology, research, academia and practitioners at the second annual Knowledge Graph Conference to discuss knowledge graphs and how they are playing a role in understanding the world. Pierre was invited to discuss how Causality Link leverages knowledge graphs to understand the impact… Read more »
In this paper, we describe a method to detect corpus incoherence on the points of view of multiple related indicators. We have described in other papers available on www.causalitylink.com how, through our universal data model of finance concepts and our natural language processing system, we are able to extract four types of data structures from… Read more »
In January 2020, during the first weeks of the outbreak, most financial analysis of the impact of the coronavirus Covid-19 have focused on the numbers of infected patients, as well as the number of deaths and remissions. These numbers are extremely important in understanding public health impact, virus propagation, and the increasing probability of this… Read more »
Financial news is a key resource for investors to base decisions on. While quarterly results are the measure of the health of a company, the experts’ interpretations of the reported numbers, as written down in financial analyses, create a lot of additional nuance. Humans are very good at collecting information from written statements, however, to… Read more »
Moody’s recent downgrade of Ford (Ticker: F) on Monday, September 9th presents an opportunity to explore whether the aggregated information contained in published financial and economics-related articles could have warned us of the strong potential for downgrade prior to Moody’s announcement. To answer this question, we did an analysis of aggregated contextual sentiment on a… Read more »