Cloud takes credit risk analytics to new heights.
The cloud-based solution is scalable and provides a 10-fold improvement over the legacy system, reaching up to 220 billion calculations overnight.
Massive cost reduction
Operating twice as fast, at one-third the cost of the legacy system, this has enabled the bank to reduce processing costs in perpetuity, and is now deploying the new platform across a further 38 locations worldwide.
Maintenance-free and compliant
Working against a strict regulatory deadline, a team of 10 from GFT delivered a maintenance-free cloud-native solution to replace the bank's legacy architecture.
Risk is an opportunity
As one of the world's most respected banks, this global giant relies on modern technology to stay ahead of the competition. To support its digitalization strategy, it needed to migrate mission-critical credit risk processing to a modern cloud environment to boost performance, reduce costs and increase flexibility.
Calculating counterparty credit risk is central to the bank understanding, monitoring and controlling its counterparty exposure. This is critical to facilitate effective trading, risk management and accounting, and to meet regulatory compliance obligations.
With new regulations effective in January 2022, the bank urgently needed to implement a new system that would boost its processing capacity five-fold with minimal interruption to business-as-usual. After careful consideration, the bank chose GFT as its partner for this transformation.
The power of partnership
GFT accepted the challenge of delivering a cloud-native credit risk data streaming and batch analytics architecture. Starting with a team of 10, GFT built a proof of concept within 12 weeks. This proved that Google Cloud Dataflow could process vast credit risk pricing and aggregation workflows.
The new cloud-native architecture replaced a legacy on-premise technology stack which struggled to process the vast amounts of data on time. From the outset, GFT designed the new solution to be flexible, scalable and fast. The new approach quickly demonstrated the speed of cloud processing with a 10-fold improvement over the legacy system, reaching up to 220 billion calculations overnight.
In addition to a HPC architecture for counterparty risk calculations, GFT expanded the scope of the platform to include what-if simulations for on-demand risk analysis to improve risk management.
A future-ready bank
With the new architecture deployed in London and Hong Kong, the bank enjoys increased levels of business agility and responsiveness. Now it can develop bespoke analytics tools, rather than relying on external vendors. This means it can shorten time-to-market to maintain its competitive edge and confidently meet regulatory compliance deadlines.
The new platform offers a step-change improvement in risk management. Traders and risk managers can run multiple rounds of accurate risk exposure numbers throughout the day, free from the worry of system constraints. The bank can model potential global stress scenarios, for example, the impact of climate change or inflation. This empowers the bank to undertake more active hedging and risk management, and to align the trading book accordingly.
The bank is now future-ready and positioned for growth. The new architecture supports dynamic scaling to support rapid trade volume growth. Critically, the solution also enables intraday risk and improved computations. The bank has reduced processing costs permanently and has deployed the new platform across a further 38 global locations.
AWS CloudFront – Content delivery network service to serve web content to customers globally with low latency and high transfer speeds.
Amazon EKS – Elastic Kubernetes Service is the runtime environment for the back-end application and Daml engine. For the MVP, the approach is to run both the back-end and Daml engine on the same EKS cluster.
Amazon S3 – Object storage is used for various tasks:
- Store and serve the AngularJS front-end application
- Store data files uploaded by the applications contributors
- Distribution channel for data provided to subscribers
Amazon RDS – Database service for PostgreSQL is used to store application and Daml ledger data.
Amazon SES – Simple Email Service to send notifications via email to all participants of the application.
AWS CodePipeline – Continuous integration and continuous delivery service connected to GitHub.
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Ground-breaking cloud native architecture to replace traditional credit risk HPC data analytics