TagniFi Tackles Investment-Grade Data

Jan 30 2015 | 7:06am ET

Big data may the phrase du jour in the financial industry, but collecting, organizing and utilizing vast quantities of data is nothing new.  In this week’s FINtech Focus, we take a look at TagniFi, which aims to make investment-grade fundamental data more accessible to fund managers and investors.

Name: TagniFi, LLC
Location: Tampa, Florida USA
Website: www.tagnifi.com
Twitter: @tagnifi
Sector: Financial Data
Year Formed: 2012
No. of Employees: 7
Stage: Seed-stage and pre-revenue

About: TagniFi is changing the financial data industry by utilizing tagged financial statements to deliver more accurate, timely and transparent financial data.

Tell us a bit about your company and what it does?

We’re developing a financial database with higher data quality, faster collection times, and lower collection costs. This new model is made possible using tagged financial statements that were mandated by the Securities and Exchange Commission beginning in 2009. Just as retail products are now scanned at checkout instead of manually typing in the price, our system can automatically convert tagged financial statements into valuable financial information.

How is different than other companies in the same space?

Before starting TagniFi we were consumers of financial data so we’ve built our company using that experience to build what we believe is a better product. Financial data is still mostly collected the old-fashioned way using thousands of analysts to comb through paper-based reports and standardize the data into a usable format. The old approach is expensive, slow, prone to error and inconsistent categorization. Our approach is built around machine-readable financial statements that allow us to collect the data immediately after its filings, more accurately, and more consistently. In addition, all of our data is time-stamped to support back-testing which is currently only available in the market from a handful of very expensive datasets.

What is your revenue model? How will the company make money?

We are currently in beta and will begin licensing our data once we cover the Russell 3000 (which represents 98% of the US market capitalization). We will offer on-demand licenses for accessing our data through an API or Excel add-in. There will be a few tiers available with the least-expensive tier starting at $99 per month. In addition, we will be offering a data feed for mass download of the entire database.

Who is your target market? How big is the opportunity?

Our target market is the “quantamental” investor who uses fundamental data in a quantitative framework. Our data was really built to meet the demanding requirements of these investors. The feedback we’ve received from our beta users has validated this to a large extent. In addition to the quantamental investors, we’ve seen a lot of interest in our data by other fintech companies who need high-quality data to power their applications or content sites. The global market for financial data is about $26 billion so there is plenty of existing demand for the product we are building.

Why are you and your team capable of succeeding?

We will succeed because we’re building a product that the market is asking for at a compelling price point. We’ve been on the other side of the table as a consumer of financial data for 10 years and we’ve seen the mistakes that other providers have made with their datasets. For example, there are some great fundamental datasets out there but most of them are not time-stamped so back-testing with these is virtually impossible. That leaves very few options for back-testable data and all of them are outrageously expensive. We know there is a market out there for financial data and we know we can build a better product. We currently have about 1,600 companies covered so we have proven that our system works. We just need to continue executing and cover 100% of the Russell 3000 in our dataset.

What is your company’s next target/milestone?

We are focused on achieving full coverage of the Russell 3000 which we expect to deliver in the second quarter. From there we will continue to add coverage for the smaller U.S. companies. In addition, we are developing some industry-specific datasets such as an oil and gas dataset that offers reserve and production information from the footnotes. Longer-term we expect to leverage this same process in different countries as tagged financial statements continue their proliferation.

Can you tell us one unusual fact about your company?

We have a copy of a Moody’s Manual from 1909 that we keep in our office to remind us of how antiquated the collection of financial data has been. There has been a lot of innovation in the world since 1909, but the collection of financial statement data has not participated in that innovation. A lot of companies are still manually collecting their data the same way it was done in 1909 and we hope to change that at TagniFi.

If you would like your fintech firm profiled, please email editorial@finalternatives.com


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