The future of Wall Street depends on structured data according to Chicago-based entrepreneur, Kevin Evenhouse, founder and CEO of NewsHedge.
NewsHedge’s recently acquired patent, “Method And System For Communicating Financial News,” covers the delivery of structured data in a way Evenhouse says human beings react to fastest — visually and audibly.
In this Q&A with Credibly, Evenhouse talked about NewsHedge technology, what it does and why he believes it will soon become standard within many different types of financial applications.
CREDIBLY: How did NewsHedge begin?
KEVIN EVENHOUSE: In 2012, I was on the floor of the Chicago Mercantile Exchange working on some machine-readable news technology.
My partners and I approached Dow Jones and RavenPack and asked if they would be interested in building an advanced news application for human consuming purposes. We were going to use RavenPack analytic data to convert that to visual graphics within news events.
You could describe what we wanted to do as Apple’s Siri for real time financial information. We were in beta, everybody was excited about the product, then Lex Fenwick came in as CEO with Dow Jones and it ended up that they squashed us like a bug and decided to launch their own news application called DJ X.
What happened next?
After we got squashed, something Dow Jones and RavenPack weren’t aware of was that we were coming across a bunch of intellectual property that we found out we should file with the patent office, which we did.
What ended up happening was we just received a full patent application this past September and as a new startup we’re trying to tell the world about that.
What does the patent cover?
The patent itself covers three different areas. Remember, we’re not a news provider. Some people get confused. We are a technology company with a bunch of intellectual property and now we’re trying to figure out what to do with it.
We’re starting to find ourselves in consultation roles and licensing technology to companies like Dow Jones, Bloomberg, Benzinga and so forth.
Talk about the three areas covered by the patent.
One of the three areas we’ve captured is Headline Automation. Headline automation uses various sources to make event headlines or notification. That could be trends on Twitter, StockTwits, or Facebook. For example, “XYZ moving on news press release or Web publication.”
It could involve market moving events like large option trades, mutual trading events or even technical. Our technology would pre-populate a template to create one simple headline about the event.
We could mention if the news has affected the underlying price of the security. We could talk about the price difference, even adding quotes into the news event stream.
That’s big because some companies are currently doing that. If they were doing it before we filed our patent in September 2012, they’re not infringing or stepping on our toes.
Many companies are now starting to add information and data into news and that’s kind of our area.
Besides headline automation, what else does this patent cover?
The second thing is Visual News Data. This involves adding graphical information to news so, for example, rather than saying sentiment is high we can say sentiment is high and then color the word high in green. Or, actually use specific graphics arrows for a box that’s green with the score in it.
The human brain, when we look at a screen of text, we’re not able to process anything because we have to read it first and then process. What we’re doing is adding graphics to news so people are instantaneously able to understand context and insight.
There’s a whole host of information you can burn into a visual news event. What is sentiment? How big is the story? Is it a breaking news event?
And the third area?
The third, Automated Voice Broadcasts, is a little more straightforward. We’re taking the structured data and broadcasting information using text to speech.
Again, think of Apple Siri broadcasting real time market events.
This product reads market data on a granular basis, looking at over 6,000 equity assets and when something unusual happens, our system reports that audibly staying, for example, “Alert! TEVA spiking higher.”
Do all three areas work together on NewsHedge?
The three areas constitute our minimal viable product, which we launched in July. The trader on the other end – we’re giving them one last thing to look at or listen to throughout the day.
The trader wouldn’t have to read the actual news event. They would have, pretty much, everything they need to know to make a decision instantly.
What’s next for NewsHedge? Development? Licensing?
We’re a small startup and ask ourselves those very questions. As I mentioned, we’re back talking to Dow Jones and RavenPack. RavenPack’s been a huge advocate of ours…we would like to have conversations with The Associated Press and Yahoo! News. The list goes on.
We’re now talking to other partners including other structured data partners. We’re also talking to StockTwits and a few others. Estimize is one we just closed a deal with.
What’s your priority, monetization-wise?
Our technology excels on the broadcast side, especially when we can broadcast something that’s happening in real time. All of a sudden, there’s an explosion of chatter on a ticker symbol or a subject on Twitter that we would like to broadcast and bring to the attention of traders.
As a startup we’re looking for the quickest path to revenue first. Right now, NewsHedge is free. People can log on and from the time when the market opens to when it closes, they’ll be alerted to unusual trading activity.
A couple of weeks ago, we launched the NewsHedge Alpha API. That is geared toward firms that want to systematically trade or build trading models. That’s our quickest path to revenue. We already have a few clients and few in beta.
We just closed an agreement with a cloud partner to start selling our data via their channels. And we also have the NewsHedge partner API, which is going to be for platformed applications such as Lightspeed or Sterling.
We may actually bring in our broadcasting technologies directly onto their platform. Then when something unusual happens, it will broadcast to their traders or clients.
The potential sounds incredible. Thinking back, what was the original inspiration point for this idea of visual representation of structured data?
At some point, it dawned on me that I wanted to do something different in finance and technology at the same time. I spent time looking at intellectual property, doing searches of past patents and patent applications.
I said, “I don’t want to build trade models. I want to visually depict structured data on the screen for traders to recognize.”
I talked with Bloomberg and Thomson Reuters and everybody was kind of like, “You want to do what? You can’t do that! Nobody’s doing that!”
They said, “We make several million dollars a quarter from this product and we don’t think we could replicate that by visually representing it on a screen.”