In complicated multivariable environments, there is no such thing as certainty.
Just like the outcome of a soccer game can be impacted by nearly every touch of the ball on the field, other multivariable environments, like a political election or a pandemic, can be impacted by innumerable factors. This makes hunting for a certain outcome a difficult task.
With certainty out of grasp, the next best thing becomes calculating probability, a far more feasible alternative. The rise of big data and artificial intelligence (AI) has radically altered the ease with which one can achieve this. With a big enough data set and a well-designed methodology, computer programs can glean hundreds of thousands of data points and categorize outcomes under certain probabilistic brackets.
Users of this technology can reap significant benefits in complicated multivariable environments, especially if competitors do not possess this information. For example, it’s easy to envision how knowing that a certain market movement is likely to occur grants traders an edge over more ignorant competitors. The problem: This information is not easy to get.
Luckily, certain entrepreneurs have made it their business to create predictive technology. Tim Hwang of FiscalNote Holdings Inc. NOTE, for example, has created a business that specializes in collecting data and repackaging it into actionable insights.
Built on popular modern cloud technology, FiscalNote’s Predata Platform leverages big data and AI to predict probabilistic outcomes in highly uncertain environments, reportedly granting their users a huge edge over competitors.
A FiscalNote Case Study: Predicting COVID-19 Movement
During the onslaught of the COVID-19 pandemic, individuals who could ascertain the trajectory of the virus had supreme advantages over others. With knowledge of the virus’s next likely destination, governments, for example, could set up proper fortifications, and investors could hedge or liquidate positions.
FiscalNote’s Predata Platform reportedly achieves this predictability goal. By measuring the finite distribution of human attention on social platforms, Predata’s patented methodology turns anonymized web traffic metadata into quantifiable measures of attention to individual narratives, topics and themes. This can then be used to predict the likelihood of events.
At some point in the pandemic, for example, the Predata platform recognized that “global interest in the outbreak was increasingly driven by Italian- and Japanese-language audiences.” The sudden spike in interest from Italian- and Japanese-speaking demographics led to a prediction that COVID-19’s next outburst would be in those areas. “Four days after the Predata alert, Italian authorities reported a sharp rise in coronavirus infections,” FiscalNote says. Predata users were sent individualized alerts of this prediction before it was vocalized by media outlets around the globe.
FiscalNote’s Predata platform has been used to make several complicated predictions, ranging from Iran’s possible retaliation to the United State’s Soleimini strike to the risk of an oil supply shock. With the tools to simplify complicated datasets and arrange them into actionable insights, FiscalNote reportedly provides its customers access to some of the most valuable information on the market — before it hits the market.
Post-midterm elections, this unique service seems more important than ever.
See how FiscalNote can help you prepare for future events here.
Featured photo by DeepMind on Unsplash
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