How We Got Started
Our team originated from the time of the Flash Crash in 2010, when a team of high frequency algorithmic traders and top scientists were convened by Dr. Leinweber, a Harvard Physicist affiliated with the Lawrence Berkeley Lab, one of the world’s largest supercomputing laboratories with 13 Nobel Prizes associated with the Lab.
The team was created to help the US Government and the Federal Reserve better understand the reasons behind the Flash Crash and potential systemic risk and spillover implications, in a time when big data and AI was nascent in financial markets.
In 2014, we decided to create the Global Algorithmic Institute as a non-governmental organization (NGO). This gave us the chance to go beyond the original mandate of analyzing financial systemic risks with a US-centric perspective. Through the Global Algorithmic Institute, we incorporate risk vectors at a global level, across environmental, socio-economic, geo-political and other dimensions. This requires large-scale Big Data and machine intelligence.
In 2015, the emergence of the Sustainable Development Goals (SDGs) provided us with a framework and a taxonomy to quantify and classify global risk factors with investing, corporate-alignment and policy implications.
Then in late 2017, we launched GlobalAI Co., a social enterprise focused on developing AI-driven datasets and analytics with a focus on sustainable finance.
Through this social enterprise approach, we’ve been able to support the NGO and implement large-scale big-data projects across multiple UN agencies and contribute to the advancement of the SDGs.