FinTech company Red Deer and TheySay, a text analytics company created by computational linguists from the University of Oxford specialising in sentiment analysis and emotional AI, are to collaborate on deep text analytics to automatically connect, contextualise and analyse research, market, alternative and social data to facilitate better investment decision-making for active investment managers.
The recent exponential growth in Big Data has meant the investment community has been struggling to keep up with a rapidly expanding data universe, making the task of filtering data in real-time and converting it into tradable insight increasingly challenging. Attempts to address these big data processing challenges have therefore resulted in a parallel acceleration in the advancement of machine learning and NLP, and it is the convergence of the two that is set to be one of the most important developments that will shape how investment firms derive value from their data and analytics capabilities in the future.
Leveraging TheySay’s advanced text analytics, Red Deer automatically analyses and provides context and relevance to huge volumes of unstructured data and text, surfacing signals within it, to provide active investment managers with real-time, tangible insights that can be used for alpha generation and to enhance investment performance. Red Deer’s notifications engine automatically alerts users to these key signals such as significant stock recommendation changes, negative or positive movements in company sentiment, as well as key management hires, all of which can impact a stock or influence an investor’s view of a company.
“We are delighted to be collaborating with TheySay on deep text analytics,” says Luke Oubridge (pictured), CEO Red Deer. “At a time when we are seeing increasing pressure on active fund managers from the fast-growing passive investment industry, empowering the buy-side with the technology that enables them to stay on top of vast amounts of data, and to intelligently connect it so it surfaces tradable opportunities, is really at the heart of what we do.”
TheySay’s proprietary natural language processing (NLP) technology reads, interprets, and tags text data to reduce the time-consuming reading and interpretation overheads that finance professionals face. Through a comprehensive multitopic and multilevel analysis of factual information as well as softer ‘human signals’ around sentiment, emotions, and more, TheySay offers richer data for predictive modelling, and enables greater forms of automation and more flexible alignment with other non-text-based data sources at scale.
Dr Karo Moilanen, CTO and Co-founder of TheySay, says: “Text data is replete with subtle and rich price-sensitive signals which can be machine-interpreted reliably only with serious natural language processing and emotional AI technology. We are thrilled to support Red Deer’s state-of-the-art platform through fine-grained information extraction and optimised deep linguistic data enrichment towards entirely new levels of personalised automation, insights discovery, and more nuanced investment intelligence.”
