CONTACT US
Case study: Data infrastructure modernization for a discretionary hedge fund
Challenge

A small discretionary trading hedge fund was operating with fragmented data systems. Trades executed across multiple brokers and insights from third-party data sources were siloed, making it impossible to generate a unified view of portfolio risk. The fund's risk manager lacked the tools to perform comprehensive, cross-platform analysis, hindering decision-making and increasing operational strain.

Solution
  • Designed an end-to-end data architecture tailored to trading operations
  • Deployed a scalable data warehouse on AWS
  • Built custom ingestion pipelines to unify broker and third-party data sources
  • Implemented a normalization layer for schema consistency
  • Automated the data workflow using AWS ECS for seamless execution
  • Developed real-time dashboards for monitoring key risk metrics
Results
  • Achieved a holistic view of portfolio risk across all brokers and data providers
  • Enabled quantitative risk analysis techniques that were previously infeasible
  • Reduced the risk manager's daily workload by several hours
  • Improved trading decisions through faster, data-backed insights
  • Established a foundation to integrate GenAI for higher decision speed and broader data integration

The fund can now monitor its positions and risk exposure in real-time, unlocking quantitative insights that drive performance. With automation in place and a clean data foundation, they are ready to scale analytics and explore AI-driven strategies.

Work with Insight Softmax

If you have a problem that can be solved with data, we can help. Our problem-solving approach works across company sizes and industries. Contact us to set up a free consultation.

Book now