- Reflexivity is a startup cofounded by two former hedge fund traders.
- It sells software to hedge funds and institutional investors to speed up the research process.
- The 4-year-old upstart just raised its $30 million Series B.
A startup looking to transform how investors and traders use data just received funding from some of the biggest names in the hedge fund world.
Reflexivity, formerly known as Toggle AI, raised its $30 million Series B in late October. Interactive Brokers and Greycroft led the round, which included participation from billionaire investor Stanley Druckenmiller and Greg Coffey, the Australian founder of hedge fund Kirkoswald. Existing investors include Millennium Management’s founder, Izzy Englander, and General Catalyst.
Reflexivity was founded by two former hedge fund traders who were all too familiar with the woes of wrangling disparate data sets to find an investing edge, or at the very least, to not miss out on an opportunity others are seizing. The startup aims to mitigate that by combining third-party data from a dozen providers like S&P Global and newsfeeds, in addition to proprietary internal information, for a full-view analysis and also flagging the potential impact world and market events may have on a portfolio.
“When you are an investor inside a major hedge fund, one big fear that is always present is that you are going to miss something,” cofounder and CEO Jan Szilagyi told BI. “It’s always exciting to have a trade that you are the only one that’s in it, but the thing that is far worse is to miss on the trade that everybody else but you is in.”
The four-year-old startup recently changed its name to more closely align with how the platform helps with the investment process, Szilagyi told Business Insider.
“Reflexivity is the act of examining one’s own assumptions, beliefs, and judgment systems, and thinking carefully and critically about how these influence the research process,” he said, referring to a term popularized by legendary investor George Soros.
Szilagyi was a portfolio manager for nearly 20 years at firms including Druckenmiller’s Duquesne Capital Management and Fortress Investment Group. The fintech’s president and other cofounder, Giuseppe Sette, also worked in asset management including a stint at macro giant Brevan Howard. They remember the investment analysis process as one that “seemed hopelessly broken” because critical data sources were fragmented and spread out across different providers and systems, Szilagyi said.
The firm estimates the potential market for its services is $16.4 billion. Reflexivity so far has about 20 institutional clients, tallying some 15,000 individual users. Clients include trading platforms like Interactive Brokers, banks, including Japan’s largest in MUFG, and several hedge funds, including Millennium Management, Soros Fund, and ExodusPoint. The startup was highlighted as one of Business Insider’s up-and-coming fintechs in 2023.
It has a valuation between $115 million and $150 million, Szilagyi said.
How Reflexivity works
The upstart’s platform lets stock-picking investors analyze data that covers about 40,000 securities from a dozen different providers, including Refinitiv and the London Stock Exchange Group, the Federal Reserve, and S&P Global. It is also built to alert customers, mostly discretionary investors who work at hedge funds and asset managers, to market events and their potential ripple effects on a given portfolio.
If there’s a big move in treasury yields, Reflexivity will automatically examine the ripple effects and see how that could impact banking stocks. In this hypothetical example, Reflexivity would see that its user, say a hedge fund trader, has Wells Fargo stock in her portfolio, and flag to her that Wells Fargo stock historically reacts very well to a rise in yields.
Behind the scenes, a proprietary knowledge graph and generative AI-powered user interface helps users connect the dots and better understand investing relationships, Szilagyi said.
Szilyagyi says he also has an answer to a question many Wall Street technologists are facing with hallucinations, or generative AI’s tendency to make up answers that are presented as fact.
Reflexivity’s answer is a so-called closed system, wherein the AI models can only pull answers from data that’s been pre-vetted by the startup. The reason other models, like OpenAI’s ChatGPT, hallucinate is because it operates on an open system that takes in data from anywhere on the internet, Szilagyi said. If it can’t find anything, it’ll be inclined to make up an answer because these tools are built to deliver some kind of answer, he said.
On top of that, Reflexivity also programmed its models to not force an answer to every question. About 5% of the time, Reflexivity will say it doesn’t have the ability to answer a given question if it’s unable to generate an answer from the data it’s been given, Szilagyi said.
“For finance professionals, the ability to get the candid and honest answer is absolutely critical because it only takes one, two hallucinations to be extremely costly when it comes to trading,” Szilagyi said.
Here’s Reflexivity’s pitch deck it used to raise its Series B.
(Because the startup only recently changed its name, these slides include its former name, Toggle AI.)
