Last week, Palo Alto California-based AI and alternative data provider Yewno, announced that it has partnered with global investment bank Citigroup, providing AI based information analysis capabilities to the bank’s data science and research units.
Basics of the Citi Deal
Artificial intelligence provider, Yewno, recently licensed its dynamic Knowledge Graph and AI-based inference engine to investment bank Citigroup, for use by the firm’s Global Data Insights (CGDI) data science team and its Citi Research unit.
Yewno’s knowledge graph aggregates and organizes huge amounts of structured and unstructured data in order to identify companies that are exposed to specific “concepts” or themes, detects hidden relationships, extracts concepts and links across varied data sources, and provides valuable insights that would have otherwise gone undetected. The Yewno Inference Engine incorporates machine learning, neural networks, and computational linguistics into an intelligent framework to enhance human understanding by correlating concepts across a vast volume of sources.
One of the benefits of Yewno’s AI technologies is its ability to help transform huge amounts of data into knowledge or insight. There is a tremendous amount of structured and unstructured data available to today’s investment professionals. Yewno’s technology can keep up with the proliferation of this data by continuously ingesting and reading full-text data from a vast array of sources, including traditional fundamental market data, global and national patents, government contracts, clinical trials, court documents, official corporate filings, news, and scientific research. Yewno then organizes this information within a knowledge graph framework so that it can be easily associated with other bits of data in ways that make sense. The result is that customers can uncover unexpected connections and insights hidden within different types of data.
A Citi executive said their decision to partner with Yewno was based on an evaluation of both NLP and Knowledge Graph technology where they decided that partnering with an external vendor was the most effective way to leverage these capabilities. They felt that the combination of a robust news feed, high quality NLP implementation, and an advanced machine learning implementation on the Knowledge Graph led them to choose Yewno for this service.
Andrew Pitt, head of Research & Content at Citi explained the rationale for this deal, “The Yewno Knowledge Graph provides us an exciting capability to analyze company exposure to trends, themes, and concepts as they emerge in the real economy and become important in financial markets. Sector and company analytics are at the core of our institutional business model and this type of Natural Language Processing and AI is becoming a necessary component of our research.”
“Citi has many projects that we will be progressing in partnership with Yewno”, explains Richard Webley, Head of Citi Global Insights. “We are expanding a proprietary thematic exposure model that tracks public companies exposure to mega-trends and disruptive innovations and Yewno will help us scale this product. We are developing thematic baskets for our investor clients and retail wealth management product teams that will introduce new views on the market on topics like ESG and emerging technologies. We also plan to expand the use of the technology to a broader range of public information like filings and patents.”
Founded in 2015, Yewno is based in Palo Alto CA with offices in New York and London. Since its founding, Yewno has raised $34.5 mln in four funding rounds, with the most recent capital raise taking place on September 30, 2018 when it raised $14 mln led by Pacific Capital Group. The firm’s core business has been licensing its AI driven products into the financial services, education, publishing, life sciences, and government sectors.
The recent partnership announced between Citi and Yewno is interesting as it is one of the first deals where a major investment bank has licensed AI technology from a third-party vendor to help enhance its research analyst productivity and generate interesting new datasets. Citi’s approach is different from some of its peers who have chosen to build their AI-driven research tools internally. For example, Morgan Stanley, after more than two years of internal development, recently announced launching its own AskResearch chatbot to help their sales staff, analysts and clients derive more of the value locked in their sell-side research reports.
We suspect other investment banks are likely to follow Citi’s lead by partnering with third-party vendors like Yewno to license and integrate sophisticated AI technologies into their research and data science efforts. This choice will enable these investment banks to leverage “best of breed” technologies, while leaving them free to focus on what they do best, produce high quality research and unique datasets for their customers.