Develop a cloud-based solution to streamline the stress test reporting metrics of the bank
- Our client is a Global tier 1 investment bank that wanted to realise the benefits of the cloud in the development of an application to manage their complex stress test calculations imposed by the UK regulator
- Previous reliance on the proprietary SAS Data Management platform and other tooling to undertake this analysis is expensive, lacking in agility and forces unwanted upgrade cycles
- Such constraints manifest themselves in significant ongoing cost and inefficiencies
- The proposal was to develop a new application built from the ground up using only native cloud technologies utilising the Google Cloud Platform (GCP)
- Develop and run the application exclusively in a cloud environment
Business process and technology alignment utilising the benefits of Google Cloud
- Using Google Cloud Platform gave access to the full suite of available technologies to build an architectural framework that would deliver and efficient, scalable solution
- Cloud Storage used as a staging area for all data entering the solution, Cloud Functions used to trigger a more meaningful notification of data arrival, Kubernetes engine used to run python code orchestration, BigQuery for data processing matches or exceeds existing SLAs
- Cloud KMS utilised to secure data in the cloud, Cloud Datalab components used to monitor and manage the extract-transform-load (ETL) workflows and Data Studio for reporting / visualisation
Efficiency and scale, with a future-proof system that can help drive growth
- The client is able to enjoy a solution that is cost-effective, flexible and highly available – able to efficiently cater for user demand at any time
- The bank has an efficient infrastructure, allowing an agile approach in demonstrating how the systems across the entire bank will operate under various stressed scenarios
- The project has delivered a significant reduction in development time compared with previous technology projects of this scale and is able to adapt easily to future requirements
