Interview with Armando Gonzalez developer of the Public Coronavirus News Monitor.
What is your own background briefly?
I’m a tech entrepreneur and co-founder of RavenPack, a leading big data analysis firm focused on the financial sector. I have devoted my career to developing Artificial Intelligence (AI) systems and solving big data problems. I’m an economist by training but have always been passionate about AI ever since I was a young boy, opening up my parent’s electronic appliances every chance I had to see what was inside them and how they worked.
Does it seem like a logical background to what you do now?
I never really thought about applying AI to finance until I started RavenPack. Financial markets present so many interesting problems to solve with data and technology. For example, most economic and financial models rely on the same fundamental and market data while failing to measure the underlying reasons as to why investors buy or sell assets.
With my training, I could have ended up working for a large bank or corporation, but instead I decided to build new models and technology that better captured these influences on investors. I was able to apply my training in finance and econometrics to design new ways to capture the necessary data to measure investor sentiment more effectively.
How was the last 12 months? What were your big wins?
The last 12 months have been some of the most intense of my career. The months leading up to the Covid-19 crisis were characterized by excitement and growth across the board. RavenPack hit an all time high in terms of revenue and customers. We grew the team in head count by 40% and moved to new modern offices in New York and Marbella, Spain. RavenPack also began closing 7-figure licensing deals with major investment banks, an important milestone and sign of our maturity as a business.
Now in the midst of the coronavirus crisis, the world seems upside down and the last few months have been all about keeping the team safe and supporting our customers during these tough times. The biggest win in these past few months has been making sure our team globally is safe and healthy. Everyone still has their job and is working well remotely. As a business, we have stayed relevant in the eyes of clients and remained productive and effective, despite the entire team working from home.
What would you have done differently?
We have always been heavily focused on research and development and putting customer needs first. We are not afraid of failing or getting something wrong, but we fail fast, and get back up and try something new. RavenPack has been a pioneer in AI, specifically in natural language processing, and there are no fully written text books or good examples to follow, meaning we have to come up with the solutions ourselves first before anyone else. I can’t say I would have done anything differently other than perhaps choosing easier problems to solve.
1 min pitch for what you are doing now?
News and social media posts, internal documents, emails, instant messages, support tickets, and other textual data contain valuable information affecting your business. However, most of this text is unused because it’s unstructured and hard to process. We solve this problem, helping users extract valuable insights quickly and easily by transforming unstructured text into structured data.
We help firms automate tedious and repetitive text classification tasks and save them time and money. What normally would take a user hours or days to do now only takes seconds with RavenPack.
We provide unique data solutions for investment and business professionals. Our award-winning data and analytics products make us the leaders in transforming unstructured content into actionable insights. By eliminating human errors such as tiredness or lack of knowledge, RavenPack reduces the rate of errors, providing a lower level of operational risk. Clients using RavenPack free up high-value resources that are best leveraged in the front lines rather than doing painstaking back-office work.
Why did you get involved with building this dashboard?
I asked the team, “What can we do to help?” We scan and analyze thousands of news and social media sites and are uniquely positioned to analyze the sentiment and key topics surrounding the coronavirus. We found that more than 80% of all news globally was talking about the virus and figured it was impossible for anyone to keep up with this information overload.
Therefore, we developed a series of news indexes to track the levels of fear, media hype, fake news, and sentiment – very much like stock tickers do to track the value and volatility of markets.
Why do you think it is such a powerful idea?
The coronavirus pandemic is a real threat to society, but so is the “infodemic” that precedes it. We need better tools and technology to make sense of the vast amounts of information, misinformation, and disinformation infecting our society today. Data analysis technologies are very powerful tools to analyze and distill the global conversation and help us understand how the pandemic is affecting us social, economically, and politically.
How bad do you think it will get for the US, especially if they go ahead and open up society again before there is a vaccine or adequate testing?
Our indexes show fear and social distancing are prevailing themes in all countries with a high number of cases, including the United States. Most people believe these measures are helping. Discussions about vaccines are at a 1-month high, as many countries disclose efforts or early results in developing a cure.
However, fear levels of a “second wave” have reached a crisis high. There is no question a rapid de-escalation of measures without a vaccine or proper testing will be accompanied by high levels of uncertainty and panic amongst Americans.
How can people find out more about you personally & your work?
The RavenPack website is a great resource for research studies, infographics, and regular insights about the work we are doing to combat the coronavirus infodemic. We also have a regular newsletter that you can subscribe to by registering for free here: https://www.ravenpack.com/page/coronavirus-insights/
I regularly make posts on linkedin and you can find my profile here: https://linkedin.com/in/armando-gonzalez-a28572b
Who and where do you get inspiration from?
I get most of my inspiration from collaborating with my team and clients. The RavenPack team includes over 120 members representing 30 nationalities. Although English is the company’s day-to-day language, altogether our team members speak over 25 languages while our developers code in over 15 programming languages. There is a high level of diversity and unique perspectives at RavenPack offering me a unique way of looking at the world when making important decisions.
We also have a highly educated customer base composed of data scientists and financial engineers (some of our clients are actual Rocket Scientists). They are very demanding and expect the best solutions, always backed by science and documented research. You can’t just “wing it” or tell a good business story, our technology needs to work and deliver quantifiable results. It’s like playing in the major leagues or competing in Formula 1 Racing.
Anything else you’d like to add / we should have asked?
Data is bigger than Oil!
We believe data is our most valuable resource and we must harness its full potential in everything that we do. Financial institutions like hedge funds, asset management firms, and banks understand the value of data and are always looking for new sources of information to generate “alpha” or higher returns. Their industry is becoming more and more systematic and data-driven, as firms hire data scientists and programmers to build fast computer programs to trade instead of relying on slower, sometimes irrational human traders.
These automated systems however, cannot read news and social media, which is unstructured text unlike most financial data out there which is structured and numerical.
RavenPack can take traditional news and social media content and turn it into structured data feeds that algorithmic trading models can consume. By pooling thousands of news and social media publishers, we are able to create an aggregate feed of content that covers all major business, economic, and geopolitical news – of interest to financial institutions.
Using NLP and other AI techniques, we can process and analyze the textual news content and turn it into a machine-readable, structured feed of analytics that computer algorithms can use to make better investment and trading decisions than humans can.
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