AI Unleashed: Revolutionizing Financial Data Collection

Hello and welcome! I'm Rachel, CEO of Intrinio. Today, we're exploring a transformative shift in the financial world—how artificial intelligence is unleashing new potential in financial data collection. We'll dive into how this surge in AI technology is not just changing the game but revolutionizing it entirely.

The Recent Surge in AI

Artificial intelligence has seen an explosive growth in recent years. Today, it’s more than just a buzzword—it's a pivotal tool in numerous industries, especially finance. AI's ability to analyze vast amounts of data quickly and accurately is opening up unprecedented opportunities for investors and financial analysts.

Imagine the possibilities when AI takes on the complex world of financial data, where data collection and cleansing have traditionally been done manually. We’re talking about a future where AI doesn’t just support decisions but transforms the very fabric of investing and data.

But before we look forward, let's take a moment to understand where we've come from.

Historical Data Collection Methods

Traditionally, financial data has been collected manually. Analysts spend hours poring over spreadsheets, charts, and reports to extract meaningful insights and populate databases. Then, they have to manually clean and normalize all the data - every quarter or every reporting period!

This process isn't just time-consuming; it’s prone to human error, limiting the speed and accuracy of data delivery.

Intrinio's Use of AI and ML

At Intrinio, we knew there had to be a better way that could speed up data collection and delivery and improve quality. We've embraced AI and machine learning to tackle these challenges head-on. 

Our technology automates the collection and standardization of financial data—up to 99.9% of it. This means not only faster data processing but also enhanced accuracy, freeing our clients to focus on what really matters—making informed, strategic decisions.

Let’s talk specifics. We’ll dive into fundamental data since it’s one of our core products.

Public companies that financial statements with the SEC have free rein to file the data using any “tags” they want to. There are currently over 75,000 “tags” being used by these filers, and it changes daily. I know what you’re thinking, and you’re right. That is a problem that AI is great at solving.

Our AI has been digesting and learning from 10k and 10q financial statements for over a 

decade, and it can systematically drop those data tags into standardized buckets. A series of 8+ machine-learning algorithms battle for the best standardization, and dozens of mathematical checks and balances are run.

There are a couple of major benefits from this AI approach to data standardization:

Speed

Our AI can clean and normalize this data far faster than a human can. We are able to deliver new filings to end users within minutes of filings going live at the SEC. This means we put actionable data in our customers' hands faster than any other provider.

Quality

Although many are hesitant to admit it, using AI to clean the data results in higher quality than humans that are prone to error. Our AI can standardize and clean data to a 99.9% accuracy without a single human intervening.

Smarter Over Time

Every time a company changes the way they file or a new tag gets added to the 75,000 index, our AI learns from it. It gets better over time and moves with the ebbs and flows of accounting standards and trends. Every quarter as it ingests more data, it gets smarter.

Flexible

Because our AI makes it so easy to instantly standardize a financial statement, it is just as easy to fix errors across the entire data set. If a bug appears, our system can fix the entire data set in a matter of minutes, while vendors taking a traditional approach have to manually adjust the entire data set. This flexibility also opens up a realm of possibilities for what we call ‘custom fundamentals’.

Affordable

Lastly, using AI and ML to solve the data standardization problem in financial services is much more affordable than hiring an army of data entry analysts. These cost savings make their way down to our customers, and they also mean we can spend our resources and time investing in making every other part of our business a better experience for our clients.

Impact on Downstream Customers & the Industry

What does this mean for our clients and the industry at large? 

For one, our downstream customers enjoy a competitive edge with access to real-time, high-quality data. This level of detail and speed enables quicker responses to market changes, better risk management, and more strategic investment opportunities. Plus, it’s light on the budget and helps them save money.

And it’s not just about individual gains. The widespread adoption of AI in data collection is pushing the entire financial sector toward more transparency and efficiency, benefiting everyone from individual investors to large institutions.

Contact Intrinio for AI-Driven Data Solutions

Are you ready to see for yourself what AI-driven financial data sets can do? Whether you're looking to understand market trends, enhance your analytics, or simply make more informed investment decisions, Intrinio is here to help.

If you’d like to learn more about our AI technology, we’d love to talk with you. Visit our website to chat with us or email us at sales@intrinio.com to learn more about how our AI-driven solutions can transform your approach to financial data. 

At Intrinio, we believe in empowering our clients with the best tools available—because when you succeed, we succeed.

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