SSI Addresses The Complexities Of Delivering Impactful Fintech And Market Data Solutions

Strategic Systems International, also known as SSI, is a software and data application developer with reaches across the business.

Founded in 1991, SSI has worked on projects As technology has grown from Web 1.0 to Web 2.0 to Web 3.0, so too has SSI. Today the company has over 220 data scientists, analysts, and engineers, and is primarily focused on providing software and data solutions for fintech firms. 

Benzinga recently caught up with SVP of Development Humayun Latif and Principal Fahad Siddiqui to talk about engineering innovative fintech products that deliver or leverage market data.

Working With Market Data

SSI’s major experience with market data started while partnering with Quantitative Analytics (QAI), a financial data company later acquired by the Thomson Corporation.

“QAI created this nice size business, based out of Chicago; although it was a successful company, they couldn’t solve some of their engineering challenges because it was such a complex platform that was taking high volumes of data,” Latif said.

SSI initially worked on QAI’s data ingestion, resolving large backlogs of data that were not efficiently being fed to end-users.

“We started by setting up a small team on the data ingestion side, bringing new feeds into the database; we demonstrated fairly quickly that we could not only ingest, but we could do it efficiently and very quickly,” said Latif. “The relationship lasted about nine years; we grew that team from four to 100 engineers; we expanded from the data ingestion side to working on three or four of [QAI’s] core products, and developing new products."

Thomson Financial ended up acquiring QAI to boost its product suite in 2006. The acquisition increased Thomson’s positioning, helping it exploit new opportunities and segments, across wider geographies, while improving client performance on the buy-side market.

Turning Social Chatter Into Signals

Beyond its solutions in Natural Language Processing, optimization modeling, machine learning, and AI spaces, SSI also works in statistical modeling and predictive analytics—deriving actionable sentiment insights for financial industry partners.

Case in point, Social Market Analytics. SMA came to SSI with a huge challenge: how to transform conversations on social networks into statistically significant metrics that could reveal financial market sentiment.

“They look at social market chatter, mainly on Twitter Inc. TWTR and StockTwits—what people are saying about publicly traded companies—and then use natural language translation to convert that conversation into a numeric sentiment score that is associated with that company,” said Siddiqui.

The information produced by the translation is then correlated to the price movement of a security, in turn revealing a sentiment based prediction on future direction.

“In fact, the software itself—the sentiment engine—proved itself to the point that it actually predicted the Brexit vote two weeks before anyone else,” Siddiqui said.

Going Forward

Latif sees exciting challenges across all platforms that are dependent on real-time, high-volume, high-velocity data, including data production/consumption, standardization, distribution and licensing.

The firm has extensive experience in the fintech space and aims to further build on its market data solutions, providing solutions for accurate and actionable trading intelligence.

“We take businesses from the idea phase, through problem-solving and strategic engagement, all the way to coming up with a product solution," said Siddiqui.