Technology Category
- Analytics & Modeling - Real Time Analytics
- Cybersecurity & Privacy - Security Compliance
Applicable Industries
- Finance & Insurance
- Retail
Applicable Functions
- Human Resources
- Quality Assurance
Use Cases
- Personnel Tracking & Monitoring
- Real-Time Location System (RTLS)
Services
- System Integration
About The Customer
The client is a global bank that offers a full range of wealth management, retail banking, and commercial banking services. It operates in more than 60 countries, has over 200,000 employees, and manages assets of about $3 trillion. The bank's commercial banking services position it among the ten largest investment banks in the world. It provides both buy-side and sell-side services to individual and institutional clients. Its trading operations deal in equities, credit, rates, currency, commodities, and their derivatives.
The Challenge
The client, a global bank with operations in over 60 countries, was facing challenges with its order management system (OMS) used for managing trade execution. The OMS provided some visibility into the trading workflow, but it lacked the ability to display aggregated information or make real-time comparisons between current activity and historical trading data. It also did not support filtering, which was crucial for traders to answer questions like the impact of new product offerings on business in specific markets. The OMS maintained multi-day open orders and data completed orders for a few weeks to allow rebooking, but it did not store and display large amounts of historical data that would enable traders to analyze trends and spot patterns in trading activity.
The Solution
The bank decided to incorporate Altair Panopticon, a real-time streaming analytics tool, into its trading infrastructure after learning about its capabilities from colleagues at other major financial services firms. A proof of concept (PoC) was implemented, involving several of the bank’s senior IT leaders and a group of senior traders and risk officers. The bank had previously implemented Kx kdb+, a specialized in-memory columnar database for handling time series data. Recognizing that Panopticon supports excellent integration with kdb-based data warehouses, the bank leveraged this capability to transition from a successful PoC to full implementation within 30 days.
Operational Impact
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