Gunja Gargeshwari is the Chief Revenue Officer for Bright Data, an industry-leading web data platform used by many Fortune 500 companies.
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Silicon Valley Bank’s collapse is much more than the first major U.S. bank default in almost 15 years. It’s also the very first implosion of a significant American bank since the financial services sector went fully digital—putting a spotlight on the critical importance of public data and, specifically, public web data to investors.
SVB’s demise provides a powerful reminder that markets react to emotional stimuli as much as objective ones. Problems with the bank’s balance sheet were well-known months before its implosion. But depositor concerns expressed on social media before SVB’s failure helped make the case that thoughtfully analyzing real-time publicly available online sentiments could have predicted the bank’s fall even earlier than objective measures of liquidity.
That’s because public data sentiment analysis has significant predictive value. Investors have a wide range of market indices to help them make decisions, such as the Dow Jones Industrial Average, consumer price index and yield spreads.
But without meaningful analysis, those are just numbers on a screen.
Data sentiment analysis, by contrast, can help financial services professionals identify early on emerging marketplace trends faster—giving them a sharp competitive edge. As a disclosure, this is one solution offered by my company Bright Data.
Quickly finding meaningful insights across the vast amounts of public web data is as critical as it is daunting. The universe of information has never been as comprehensive and accessible as it currently is.
Each day, companies churn out reams of live public data. Some of this data they tout proudly and some they try to bury. Simultaneously, governments and financial organizations produce economic data that impacts a range of industries, providing possible valuable clues about where the market may be headed.
Consumers, too, are prolific generators of data. Through public social media posts, blogs and other forums, they provide clues that reflect consumer confidence, market trends and opportunities. Demographic and economic data can help assess market risks now, in real time.
This makes the difference between knowing how to safely navigate this volatile reality and simply relying upon gut feeling.
There are literally billions of data points in existence.
Accessing, aggregating and analyzing that data is another matter. That’s where automating data sentiment analysis and smart intelligence gathering come into play. Here are four strategies for leaders seeking to implement data sentiment analysis solutions in their organizations.
1. Hedge funds, private equity firms and investment banks can now acquire, distill and analyze vast amounts of public data to make the most intelligent investment decisions. That includes a range of sources, including customer sentiment, competitor analysis, pricing insight and social media data.
2. With a strong data gathering platform, investors can gain a glimpse into the future. For example, if an investor chooses to invest in a retail company, data sentiment analysis can enable them to forecast what future pricing positions will look like compared to competitors.
3. Financial services professionals of course aren’t web data experts. That’s why Wall Street players are increasingly turning to solutions that can access and collect public data for them in the smartest, fastest and simplest manner possible.
Investors should prepare themselves to provide the schema for their intelligence gathering needs. Collected and analyzed well, data scientists can aggregate comprehensive datasets to substantially improve decision making.
4. To make data collection and analysis as easy as possible, data analysis solutions providers are working toward offering new tailored products that allow investment firms to access the precise public data they need on their own. Leaders should continue to seek solutions capable of independently collecting public information without having to maintain the technology on an ongoing basis.
SVB’s collapse is just one symptom of deeper challenges in today’s marketplace.
Identifying the risks and opportunities requires unlocking and understanding publicly available data. One incontrovertible truth hasn’t changed throughout history: Those who make decisions using the best and latest information will have the upper hand in the marketplace. More often than not, that data is hiding in plain sight, waiting to be accessed and analyzed. I hope this article offers some valuable takeaways for leaders seeking to implement data sentiment analysis solutions in their operations.
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