Below is an excerpt from Eagle Alpha’s 2023 annual report. Their full report includes more granular industry trends, data sourcing, leading case studies, and technical product updates. Click here to request the full report.
As we close 2023 in the alternative data industry, we reflect on a polarized year of macro uncertainty coupled with technological innovation. It is a year characterized by an interplay of robust supply dynamics and nuanced demand patterns where the investment community has had to contend with rising interest rates and a year of anticipated recession risk.
Three years ago, we had to contend with a global lockdown and this year a threat of recession, political instability on the global stage and AI disruptors. Despite this, the supply dynamic of the market is as compelling as ever and the level of innovation on the demand side could herald further advancement of the adoption curve.
Data Sourcing Perspectives – A Look at 2023
Data Sourcing at Eagle Alpha had another busy year.
We grew total datasets by over 17% and by year end we will have added over 250 new datasets to the platform, all with a detailed profile and attached DDQs. The chart below includes new data vendors and new datasets added by existing vendors.
Figure 1: Dataset Growth by Category (Source: Eagle Alpha)
LLMs and ChatGPT
From a data sourcing perspective, there have been a few dominant themes this year. No prizes for anyone to guess what dominated conversations this year… yes, LLM and NLP. In last year’s annual report, we highlighted the fact that even before ChatGPT was released there was a fair amount of interest in access to data sources across news, transcripts and filings. This continued in 2023, but attention also shifted quite a bit as the year progressed.
Early this year we began to talk to most of the established NLP vendors about the threat of open LLMs and chat functionality. Most of the vendors recognized that things had changed and were quickly jumping on open models to enhance their workflow and data products.
Some others seemed to be slower but did show evidence of pivoting as the year progressed. On the buy-side there was a lot of interest in what these NLP vendors were doing and around Spring a notable shift began to happen. Funds were looking to quickly get to grips with the topic. Our take initially was that it became less advanced NLP using your own data inputs to build sentiment and signals and more of an efficiency play.
“How can I use ChatGPT and other models to gain an efficiency advantage?” Broadly this is summarization, prompt and Q&A that can make any analyst or PM more efficient. This then morphed into “how can I bring my own internal data to a model” but, critically, without risk of data leakage.
On this market-driven demand, many of the vendors did another pivot and opened up their domain knowledge and products to an NLP-as-a-service offering. On the one hand, using a ChatGPT-like functionality and then on the other providing LLM services in a secure cloud or on-prem environment. This is a very dynamic space right now. Things are changing rapidly, and it is going to take some time to play out.
You are invited to download the report. Eagle Alpha’s full report includes more granular industry trends, data sourcing, leading case studies, and technical product updates. Request report here.