Alternative Data Weekly #237

May 9, 2025

John Farrall

May 09, 2025

Thanks for being here!

Thanks to this week’s sponsor: InnovAItion.io

AI Solutions for CX and Contact Center Business Process Optimization. Contact Kevin Murphy.

The theme that emerged in this week’s email is … the pace of change is accelerating. There is a lot to digest.

QUOTES

“Alpha—that coveted excess return—behaves like a mirage in the financial desert: visible to all yet attainable by few. While countless quantitative models and qualitative frameworks attempt to capture it, generating sustainable alpha first requires understanding the complete data-to-decision journey that creates it.” - The Terminalist

News Articles
Podcasts
Cool Charts
Final Thoughts (Smart Brevity)

#1– J. Scott Hamilton published The Birth of the Data Grid. April 2025.

My Take: The first thing that resonated with me from this article is the idea that AI is killing the value of “knowing something others don’t. It’s in discovering what no one’s seen yet.”
Context is essential and core to how knowledge workers will engage with information.
The second concept that resonated with me is around data pricing. Metered access to data in some fashion would expand access to data assets. Similar to what Snowflake did for compute.

#2 – Guiseppe Sette published Plotting the future of AI in wealth and asset management. May 2025.

My Take: The author addresses AI’s impact on asset selection, risk management, and hyper-personalization.
All are relevant and huge opportunities, but as the author indicates, and I see in the market, is the impact on risk mitigation. Risk mitigation is the low-hanging fruit opportunity and lowest risk (ironically?).
The hyper-personalization aspect is of most interest to me, as that is our focus at ModuleQ. There is a lot that can be done with AI to help wealth advisors & relationship managers provide better, more personalized service.

#3 – Joe Gits published AI Developments for the Financial Services Industry. April 2025.

My Take: The author describes the bringing of workflows in-house, replacing expensive vendors & simplifying business user engagement.
This can deliver a better user experience, but not simple (yet).
Those “AI vendors” I have seen gain traction are those who are focused on delivering a very narrow solution, & one that works to solve some specific problem.
There is huge upside as those solutions expand and get more flexible.

BONUS: Alysa Taylor published How real-world businesses are transforming with AI — with 261 new stories. April 2025. Here are stories of over 700 (seriously, 700+) companies using AI. Enjoy reading all those.
It is interesting how many times the term “hyper-personalized” is used and “proactive” … two areas that are hot and getting hotter.

What else am I reading (many good articles this week):

Abraham Thomas published Data and Defensibility. April 2025 (third and final repost … check it out)

McKinsey published How Gen AI Is Transforming Market Research. April 2025 (repost from last week…good article)

McKinsey published The missing data link: Five practical lessons to scale your data products. April 2025.

Sydney Blanchard published Acceldata’s Adaptive AI Anomaly Detection Supercharges Data Quality. April 2025.

Dave Yuan of Tidemark Capital published Beyond the System of Record: Becoming an Industry Ledger. No date provided.

Ben Lorica published The troubling trade-off every AI team needs to know about. May 2025.

Ergest Xheblati published Understanding Business Context. May 2025.

Sven Balnojan published AI states the obvious. April 2025.

Vote for David Brunner!

Source: Joe Reis interviewed Sarah McKenna, CEO of Sequentum: Web Scraping Explained. April 2025.

My Take: I enjoyed this conversation. Sarah knows her stuff.
They start with a great overview of the “alt data” space and web scraping. Sequentum has a platform that makes it very easy. The game is (always) changing.
They had an interesting conversation about the cat & mouse game between bot blocker & scrapers at minute 13:00.
How is AI changing the web scraping industry? Sarah shared an example of risk alerting driven by LLMs. You still need to handle all of the thousands of edge cases … this is where legacy web-scraping companies have an advantage.
Lastly, they had an interesting conversation about culture in the industry.

Highlights (60-minute run time)

Minute 01:00 – what is web scraping?
Minute 03:30 – how did Sarah get into web scraping?
Minute 06:00 – Sarah describes “alt data”
Minute 11:00 – privacy & tracking online behavior (cookie-less)
Minute 13:00 – the cat & mouse game between scrapers & bot blockers
Minute 16:00 – crawlers vs scrapers; LLMs being used to confuse crawlers; using a “full browser”
Minute 20:00 – building a scraper from scratch (btw … just use Sequentum)
Minute 23:30 – how is AI changing the web scraping industry?
Minute 28:00 – how to determine the quality of the data that is collected?
Minute 34:00 – culture of sharing in the industry
Minute 36:00 – scraping with an LLM (pros & cons); lots of noise
Minute 44:30 – scraping copyrighted data
Minute 49:00 – implication for content creators

Source: The Terminalist published Post-Terminalism: AI and the rise of a new frontier. April 2025.

Another great, dense article by the Terminalist. Thanks for sharing this in public. This was published April 11 … took me almost a month to get through it. #worthit

“Herein lies the post-terminal distinction: data and information are commoditized system outputs stating facts that are equally available to all terminal users simultaneously. Insights, in contrast, are uniquely inferred from information and specific to the user who inferred it. Thus anything widely distributed becomes information, leaving anything personally inferred using individual judgment to become insight.”

This is where ModuleQ sits.