Today, investment professionals work in a state of information overload, facing an ever-increasing abundance of information. Current tools do not allow investors to process such vast amounts of information effectively, which leads to biased or simply erroneous investment decisions. Exabel's innovation is an intelligent modeling platform that uses state-of-the-art Artificial Intelligence methods and mathematical modelling techniques to help investors turn the massive streams of data into actionable insights. The FinAI project will conduct the necessary research for the modeling platform. Our system will support analysis across thousands of exchange-listed companies to surface insights that are tailored to our end users' needs. This will be achieved by an automated model-building framework supporting various types of models at a massive scale. The main issue is one of generating relevant insights from the raw data flows: processing the data inputs effectively and then building models that best explain the observable patterns in financial markets. We have structured two areas for which research is needed: 1) Extracting structured information from natural language (NLP) 2) Quantifying the effect of information through model building The tool will be optimized for model building on large non-homogenous data sets. It will be unique in the way it supports analysis of a broad range of data sets including what’s referred to as Alternative Data, to identify patterns that are intelligible only via state-of-the-art data science techniques.
Project leader: Øyvind Grotmol
Institution: EXABEL AS