A Capital Markets Regulator Modernizes Risk Platform to Improve Compliance
The solution increases development velocity by leveraging Infrastructure as Code.
The client is one of the world’s leading fixed-income managers. With a focus on long-term fundamental value investing that employs a top-down and bottom-up approach, the client has been recognized for emphasizing team management and intensive proprietary research supported by robust risk management.
The client embarked on a technology modernization initiative to optimize the investment management process further. The first step was to re-architect their real-time pre-trade compliance engine to achieve scalable performance, modern architecture for enhanced portfolio management optimizations, and a high-velocity development process. The re-architected system had to support simultaneous trades, each with hundreds of accounts and each account often having dozens of specific guidelines. Also, the system needed to be robust enough to handle the vast amount of data with data and inter-trade dependencies processing in real-time. Peak computation alone took millions of calculations per second to achieve prompt response times, not including timely data delivery.
To meet the challenge, Ness leveraged a Kafka-based streaming architecture and developed a repeatable pattern for stepwise technology modernization, enabling the transition to the cloud without business disruption. We recommended AWS as the infrastructure solution and designed a Re-Orchestration and Data Modernization architecture to achieve near-perfect parallelism, allowing the client to increase capacity at peak times with a throughput of just one second as overall trading volumes and automation algorithms grow. The AWS-based infrastructure increased the stability, resiliency, fault tolerance, and cost savings.
The client achieved a near-perfect scaling of all 1.5 million calculations. The solution increased development velocity by leveraging Infrastructure as Code, allowing each developer to test variable configurations of a Confluent Kafka and Flink application in AWS. Ness also established a brand-new data governance process leveraging Confluent Cloud and Kafka Schema Registry.