The Client is a Fortune 500 company, a leading multinational investment bank

Business Problem

The Client wanted to enhance legacy P&L generation platform that was plagued with multiple issues:

  • Onboarding of high-volume Algo-trading customers: High-volume transactions were processed through traditional RDBMS based DB system impacting onboarding.
  • Scalability: Existing architecture relied on a legacy database for all data extraction use cases. Application scaling was a challenge, and this put the database under heavy stress while processing the transactions.
  • Real-time reporting: Lack of a robust reporting solution limited the visibility into various processing parameters.
  • Outdated systems: Rapid fetching and loading of prices for all products was done on the legacy platform. This was becoming a challenge and laborious.

The Solutions

  • Solution built on a “distributed cache system” to cater to extremely high volumes (>500K rows) of transactions
  • Built a new In-memory data grid solution that aggregates & transforms the data in-memory and provides paged results and in real-time.
  • Customized snapshot data for a configured period from the current business day.
  • A pricing solution was built using micro services and NIO architecture to cater to a huge volume of products and the ability to configure new price sources.
  • Solution facilitated the data push to the downstream systems.

Value Delivered

  • P&L generation platform can now handle more than 2M requests per day
  • Reduced latency of High-volume reporting to less than 5 seconds.
  • Real-time processing of more than 500k transactions per minute.
  • Significant improvement of UI/UX experience of the screens because of integration with the new platform.

Get in Touch

video close