We sat down with Andrew Lobos, SVP of Licensing at Benzinga, to talk about how real-time financial data, AI, and the next wave of fintech are colliding in ways that affect every investor — not just the hedge funds.
Here’s something most people don’t think about: every time you open your Robinhood app and look up a stock, almost everything you see on that page — the earnings, dividends, analyst ratings, news feed — that data came from somewhere. It was licensed, structured, and delivered in real time by a company like Benzinga.
That’s what Andrew Lobos does. As SVP of Licensing at Benzinga, he sits at the intersection of financial media, raw data, and the AI platforms that are increasingly consuming all of it. We had him on Deconstructing Data recently, and the conversation went in directions I didn’t expect.
The Market Is a Firehose of Data — And Timing Is Everything
Most of us interact with financial data in a pretty passive way. We check our portfolios, maybe read a headline. But for the institutions and platforms that Benzinga serves, real-time market data isn’t a nice-to-have. It’s the entire game.
“The market itself is so dynamic. Whether you’re a long-term investor or a day trader or a multibillion dollar hedge fund, you have to know what’s going on. You have to know how the earnings went, what’s happening politically, the economic calendars, the IPOs. The market is just a conglomeration of data — and we try to get it to people as fast and as accurate as we can.”
— Andrew Lobos, SVP of Licensing, Benzinga
What’s changed is who’s consuming that data — and how. Robinhood recently announced an MCP-based automated trading solution. A year before that, they launched Cortex, their AI-powered stock summarization tool. The pattern is clear: brokerages are racing to wrap AI around financial data to make it actionable for the average investor.
Andrew put it simply: the idea is becoming more powerful than the skill.
“If you wanted to high frequency trade before, you would have had to hire someone with an engineering background to set it up. Now you can just tell the agent the exact strategy you’re looking to deploy. The idea now is more powerful than the skill.”
— Andrew Lobos, SVP of Licensing, Benzinga
That’s a line worth sitting with for a minute.
The “Commoditization” Panic — And Why It Didn’t Happen
When AI first exploded onto the scene, everyone in the financial data industry had the same reaction. Andrew described it plainly:
“When AI first hit the scene, everyone in our space was freaking out. They were like, ‘All of our data is commoditized. People are going to scrape it themselves, vibe code a streaming solution of earnings, and they won’t have to buy it anymore.'”
— Andrew Lobos, SVP of Licensing, Benzinga
It didn’t play out that way. Here’s why: what makes financial data valuable isn’t the raw signal — it’s everything layered on top of it.
Benzinga’s news desk isn’t just scraping press releases. They’re staffed by writers trained on the history of finance who have direct relationships with CEOs and sell-side banks. They can pick up the phone and get a quote that no AI agent could get. That’s proprietary. That’s the moat.
“The value in our data is the additional insights and enrichments that we have added. What you do with the data is what provides the value to the end user.”
— Andrew Lobos, SVP of Licensing, Benzinga
They took analyst ratings — something plenty of vendors provide — and built aggregations on top of them. Then summaries. Then summaries of the reports. Then a bull and bear case for each stock. Layer by layer, they created something that couldn’t just be replicated by pointing a bot at a press release feed.
The lesson here applies way beyond fintech. If you have a data set, the question isn’t “can someone else get this data?” The question is “what can we add to it that they can’t?”
Where Fintech Is Actually Headed
I asked Andrew to take a shot at predicting the future — one year out, five years out. He was honest about how hard that is in this industry (“it’s like the wild west”), but he landed on two things he’s confident about: education and personalization.
On education:
“I hope that more people will be educated on personal finance and investing because we’re breaking down the barrier to information and understanding.”
— Andrew Lobos, SVP of Licensing, Benzinga
This resonated with me. We don’t teach personal finance in school. As AI makes investing more accessible — easier to understand, easier to act on — the hope is that more people actually take the wheel on their financial futures instead of just letting their 401k sit on autopilot.
On personalization, Andrew made a point that stuck:
“If you go on Instagram or TikTok, it’s so highly tailored to what you want to see. You’re never choosing what you want to see — the platform knows. Fintech and finance have not done that yet. When you go on your brokerage or your 401k, it’s the same homepage every single time. I foresee a world — especially with AI — of personalized summaries and a better personalized experience.”
— Andrew Lobos, SVP of Licensing, Benzinga
If you know I’m a long-term investor who cares about tech stocks and the S&P, why are you showing me meme coin coverage? The platforms that figure that out first are going to win.
Practical Advice for Anyone Sitting on an Interesting Data Set
One of the most useful parts of the conversation was when Andrew gave some straight talk to anyone thinking about monetizing a data asset in the financial space.
The opportunity is real — hedge funds and institutions have entire teams whose only job is to find new data sets. They’ll test almost anything. But the bar is high.
“You need at least three to five years of history on the data set for these hedge funds to even consider it. You need consistency in delivery — if you say it’s a daily data set, you can’t miss a day. There can’t be any anomalies. And all of the additional costs — the storage, the insurance needed to distribute to a hedge fund — it creates a barrier to entry.”
— Andrew Lobos, SVP of Licensing, Benzinga
His advice? Don’t lead with the hedge funds.
“I would suggest finding a way to monetize it outside of finance and use finance as your second wind — or your third, or your fifth. Make sure you have a viable business plan and consistent sticky customers, and then approach the institutions.”
— Andrew Lobos, SVP of Licensing, Benzinga
Benzinga itself didn’t plan it this way — they were a news company first, started licensing data almost as an afterthought, and happened to have three years of history by accident. That history is what let them compete for institutional business.
The AI Angle No One Talks About: Enriching Your Own Data
Andrew shared a story that really drove home how much has changed. Benzinga has a data partnership that tracks TV viewership. A client asked for their top 1,000 TV shows — no problem. Then they asked for categories. Problem: the data set had no categories.
Old solution: all-nighters, contract workers, weeks of work. New solution: drop the spreadsheet into Claude, ask it to categorize each show, get results in seconds.
“I looked through it and it was really good. We just added value to the data set because now we can group them — I can tell you every household that watches sci-fi. And four years ago, you would have been pulling all-nighters and hiring contractors to do that.”
— Andrew Lobos, SVP of Licensing, Benzinga
That’s the story of AI right now. It’s not replacing the data or the strategy. It’s collapsing the time it takes to turn raw material into something useful.
The Bigger Picture
We talk a lot on this show about data — consumer data, marketing data, identity data. What I found refreshing about Andrew’s world is how clear the value chain is. Real-time financial data powers decisions that move actual money. The feedback loop is immediate and measurable in a way that a lot of other data categories aren’t.
But the underlying dynamics are the same: raw data is becoming a commodity, the moat is in the enrichment, and the companies that figure out how to structure and distribute their data assets intelligently are going to win.
Andrew said it well near the end of our conversation: he’s been in this industry seven and a half years and he can see himself staying until retirement — because it never stops changing.
That’s how I feel about data broadly. The rules keep shifting, and that keeps it interesting.
Want to explore what Benzinga’s financial data can do for your platform? Visit benzinga.com or connect with Andrew Lobos on LinkedIn.
This article was adapted from an episode of Deconstructing Data, BDEX’s weekly podcast on data-driven marketing. Tune in live every Thursday at 4:15 PM Eastern on LinkedIn.
About BDEX: BDEX helps brands build authentic connections with their audiences through the power of data and AI. Visit bdex.com or click “Talk to an Expert” to get started.
