Real-Time Market Analysis Platform

about task
In the fast-paced world of finance, every second counts. Our client, a leading financial institution, faced the formidable challenge of navigating the volatile waters of the global markets. With vast amounts of real-time market data, news sources, and social media sentiment flooding in, they needed a solution that could turn this data deluge into a strategic advantage.
Reviewed on
5/5
30,000
+

Hours delivered back to the business

100
+

SOX compliance in Settlement process automation

95
+

Success rate of bot case completion

6
+

For functional release of OBT, RTS and OGS

The Chalange

The primary challenge lay in the sheer volume and velocity of data. Our client needed to process, analyze, and derive actionable insights from an ever-flowing stream of market information. They sought a way to swiftly identify market trends, assess sentiment, and respond decisively to emerging opportunities or threats. Staying ahead of competitors in this highly competitive arena required more than just data; it demanded real-time insights.
  • Data Overload: The client faced the challenge of processing and analyzing vast amounts of real-time market data, news sources, and social media sentiment.
  • Lack of Insights: There was a need for actionable insights to inform trading decisions and respond rapidly to market trends.
  • Competitive Edge: Staying ahead in the highly competitive financial industry required a solution that could deliver a competitive edge.

What We Did

  • Robust Data Aggregation: We built a robust data aggregation system capable of collecting, filtering, and storing real-time market data from multiple sources.
  • Advanced Analytics: Implemented advanced analytics algorithms to process news articles and social media posts for sentiment analysis and trend identification.
  • User-Friendly Dashboard: Developed an intuitive and user-friendly dashboard that presented real-time insights and allowed traders to customize their view.
  • Predictive Modeling: Leveraged predictive modeling to anticipate market movements and generate automated alerts for specific conditions.

The Results

The technology that we use

JavaScript
TypeScript
Node.JS
React
Swift
Java
Objective-C
RxJava

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case studies

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