Interview with Armando Gonzalez CEO of RavenPack - The Present and Future of Financial Markets: Fintech, Big Data, Analytics, AI Machine Learning

Interview with Armando Gonzalez CEO of RavenPack – The Present and Future of Financial Markets: Fintech, Big Data, Analytics, AI Machine Learning

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By Dinis Guarda

Armando Gonzalez, CEO and Co-Founder, RavenPack tells us about The Present and Future of Financial Markets: Fintech, Big Data, Analytics, AI Machine Learning in this new interview.

Armando Gonzalez is a technology entrepreneur and the CEO and Co-founder of RavenPack, the leading provider of big data analytics for financial institutions. At RavenPack, he oversees all product design and engineering of the company’s data products and analytical tools. Armando is a recognized expert in applied big data and artificial intelligence (AI) technologies. He is widely regarded as one of the most knowledgeable authorities on systematic data analysis in finance.

Interview focus

1. An introduction from you - background, overview, education...
2. Career highlights
3. Your company, organisation and focus
4. What are your work priorities
5. Goals and how do you see the future of work and the main trends in tech and society
6. With Covid-19 how can you look at this as a way to redesign our society

Quotes and notes

· Evolution of financial technology and data for financial markets. In that regard, technology infrastructure is critical for capital markets. They bring something new to the analytic data table. The importance of sentiment analysis for capital markets and financial industry.

· ESG can be a potential source of alpha for equity investors. Our latest ESG study shows how sentiment analysis enhances stock screening, leading to better performance and downside risk mitigation. For example, stocks with a high ESG rating tend to experience lower drawdowns during periods of negative news around ESG issues, and, more importantly, when they do sell-off they usually overshoot temporarily before making a recovery. This suggests that by timing stock purchases until after the release of negative environmental news caused a temporary pull-back in price, we can further enhance returns.

· Main trends - governments still being driven by governments - central banks; investors are depending of macro decisions by governments

· Predicting capital market values is one of the most challenging use cases for AI. NLP and nuances of language are critical for solving problems. How machine learning can take action and mimic our decisions and actions.

· Global finance has reached a critical inflection point as asset owners and money managers embrace tools like machine learning and big data analysis to navigate complex and turbulent markets

· The basics is taking unstructured data and turning in metrics

· We have access to 1 million websites and news financial sources. The team picks the data and sources with resources and reputation and foundation of information. This collects the data to an environment that classifies and tags information and creates statistics based on machine learning. We create a tag in less than milliseconds. Speed, accuracy of tech and data and research and finance and economy and next phase grow data.

· As Ravenpack seeks to expand outside financial services does this give you an advantage over existing suppliers in those sectors. Being one of the first alternative data providers, founded over 17 years ago, we had a head start in looking at solving problems in the financial industry initially and after in bigger areas like retail and other areas, developing analytics and expertise.

· Global finance has reached a critical inflection point as asset owners and money managers embrace tools like machine learning and big data analysis to navigate complex and turbulent markets, consequently, we are experiencing significant growth in demand for our unique data services in Asia.

· Ravenpack technology is mature and we have many projects going on that further push the boundaries of what is possible in automated text and unstructured content analysis. We built everything with low latency at its core, making our engine the fastest “text processor” in the world.

· These fundamental qualities and growing demand from corporate customers mostly now banks, asset management, central banks and going forward outside of finance certainly gives us an edge over suppliers, and I would argue, even above some of the Goliaths in our space.


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Armando Gonzalez Biography

As co-founder, Armando Gonzalez established RavenPack as a premier firm in sentiment analysis and natural language processing. A graduate of the American University of Paris, Armando started his career in finance and economics after venturing into market inefficiencies caused by information arbitrage. His research led to designing systems that turn textual news into data that can easily be consumed by quantitative models and trading programs.

He is a recognized speaker at academic and business conferences across the globe. Armando holds degrees in Economics and International Business Administration from the American University in Paris. As a thought leader, his commentary and research has appeared in leading business publications such as the Wall Street Journal, Financial Times, among many others.

Armando is widely regarded as one of the most knowledgeable authorities on automated news and sentiment analysis. His commentary has appeared in leading business media such as the Wall Street Journal, Dow Jones Newswires, CNBC, The Trade News, among others. Armando is a recognized speaker at conferences on behavioral finance and algorithmic trading across the globe.

Specialties: Financial technology, news analytics, sentiment analysis, machine-readable news, algorithmic trading, quantitative analysis, natural language processing (NLP), financial data feeds, team building, product development, business development, strategic planning, market sizing and analysis, competitive intelligence, fund raising, and project management.

About Ravenpack

Ravenpack is a company that focuses on big data analytics and machine learning using NLP for financial markets. The company’s database, comprising over 19,000 sources spanning over 20 years, is used by financial institutions who subscribe to the platform in order to enhance performance and manage risk. RavenPack will use the proceeds to expand in Asia, as well as to go into other sectors beyond financial services.

RavenPack’s platform is used by some of the best performing hedge funds and largest banks worldwide. RavenPack uses AI to turn highly fragmented unstructured content into organised structured data for easier analysis and deployment in financial applications. The firm has a team of more than 100 people and offices in New York City and Marbella, Spain.

Per Roman Managing Partner at GP Bullhound, says about the company: “I have had the pleasure of getting to know Armando and his team in the last four years and have in that period seen RavenPack mature into possibly the most interesting natural language processing and machine learning company in the world. It is therefore a pleasure to join as a shareholder and board member in the next chapter of growth and expansion.”

Data analytics based on artificial intelligence (AI) is already widely used in algorithmic trading, and RavenPack is moving into other areas of financial services. Financial advisers and private equity and venture capital firms have all begun using the Marbella-based company’s services, he said.

Machine learning and AI have the capacity to transform a range of activities from identifying targets to optimizing negotiating strategies, Roman said, adding that none of them will be fully automated.

GP Bullhound has invested in RavenPack through Fund IV, which focuses on growth stage business in the software, digital media, marketplaces and fintech sectors. Recent investments include Slack, Klarna, Tradeshift, Glovo and Believe.

With +130 team members across our New York and Marbella (Spain) offices. "We were only 40 “RavenPackers” two years ago and every department, from Development to Operations, has grown dramatically. What is really exciting is that all this growth has been supported by revenues, and we want to keep it that way. Therefore, we need to ensure we continue developing cutting edge data products and keep pushing the state of the art with ongoing research and development efforts. We also have VC backers whose funding is fueling many of these innovation projects - keeping us ahead of the game"

Links and quotes

https://www.linkedin.com/in/armando-gonzalez-a28572b/

https://www.crunchbase.com/person/armando-gonzalez

Interview: Armando Gonzalez, CEO, RavenPack https://www.aidatatrading.com/blog/interview-armando-gonzalez-ceo-ravenpack#.XsuplnloksU.twitter

GP Bullhound invests USD10m in RavenPack

http://www.hedgeweek.com/2019/10/28/279888/gp-bullhound-invests-usd10m-ravenpack #Deals & Transactions #Investments #Services #Research & Analytics

GP Bullhound Invests $10M in US Data Firm Ravenpack

https://www.businesscloud.co.uk/news/gp-bullhound-invests-10m-in-us-data-firm-ravenpack

Turning alternative data into invaluable insights and enhanced returns.

https://www.gpbullhound.com/investment-management/turning-alternative-data-into-invaluable-insights-and-enhanced-returns/

The Handbook of News Analytics in Finance

https://books.google.co.uk/books?id=oL2XUi60pAAC&dq=Armando+Gonzalez,+CEO+and+Co-Founder,+RavenPack&source=gbs_navlinks_s

M&ATech: Data analytics could prove transformative for M&A practitioners – experts

https://www.gpbullhound.com/news/news/matech-data-analytics-could-prove-transformative-for-ma-practitioners-experts/

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