๐Ÿ‡ฆ๐Ÿ‡บStalecollected in 2m

CBA migrates decade of data to cloud for AI

CBA migrates decade of data to cloud for AI
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๐Ÿ‡ฆ๐Ÿ‡บRead original on iTNews Australia

๐Ÿ’กLearn how a major bank scales infrastructure to support enterprise-wide AI analytics.

โšก 30-Second TL;DR

What Changed

Migration of over a decade of historical data to cloud platforms

Why It Matters

This migration allows CBA to leverage cloud-native AI tools on massive datasets, significantly reducing latency for predictive modeling. It sets a benchmark for legacy financial institutions modernizing data stacks for AI.

What To Do Next

Audit your own legacy data pipelines to identify bottlenecks that prevent cloud-native AI model training.

Who should care:Enterprise & Security Teams

Key Points

  • โ€ขMigration of over a decade of historical data to cloud platforms
  • โ€ขStrategic infrastructure upgrade to support AI-powered analytics
  • โ€ขEnabling scalable data processing for enterprise AI workloads

๐Ÿง  Deep Insight

Web-grounded analysis with 23 cited sources.

๐Ÿ”‘ Enhanced Key Takeaways

  • โ€ขCommonwealth Bank of Australia (CBA) has migrated over 10 petabytes of data and 61,000 data pipelines to Amazon Web Services (AWS), completing what it claims is one of the largest and fastest data migrations in the Southern Hemisphere.
  • โ€ขThe migration extends to CBA's core banking system, making it the first major Australian retail bank to fully transition its core operations to the public cloud, replacing its legacy mainframe infrastructure.
  • โ€ขCBA currently leverages AI to make approximately 55 million decisions daily, utilizing over 2,000 AI models that process around 157 billion data points.
  • โ€ขThe bank has developed an internal multi-agent AI platform named 'Lumos' to automate and accelerate application modernization, boosting the modernization velocity from 10 applications per year to 20-30 applications per quarter.
  • โ€ขCBA has established an 'AI Factory' powered by Amazon EC2 P5 Instances, providing high-performance compute capacity to accelerate generative AI innovation and enable engineers to safely test and develop AI solutions.

๐Ÿ› ๏ธ Technical Deep Dive

  • Cloud Provider: Amazon Web Services (AWS) is CBA's preferred cloud provider.
  • Data Migration Scale: Over 10 petabytes of data and 61,000 on-premise data pipelines were migrated.
  • Core Banking System: Migrated from mainframe infrastructure to AWS-managed data centers.
  • Data Lake: CBA's data lake, previously hosted on Snowflake within AWS, has been brought into closer proximity with its core systems on AWS to improve AI performance and efficiency.
  • Data Architecture: An AWS-based data mesh ecosystem, branded as "CommBank.data," has been established, featuring a federated data architecture that enables self-service data access for 40 lines of business.
  • AI Platforms/Tools:
    • Lumos: An internal multi-agent AI platform used for application modernization, integrating with AWS services such as Bedrock, ECS, and OpenSearch.
    • AI Factory: Powered by Amazon EC2 P5 Instances, this factory provides high-performance computing for fine-tuning large language models (LLMs) and developing AI solutions.
    • CommBiz Gen AI: An AI-powered messaging service built on the bank's DevOps Hosting platform and Group Generative.AI Platform, utilizing Amazon Bedrock Knowledge Bases, Claude 3, Cohere LLMs, and Amazon OpenSearch.
    • Partnerships: Collaborations with H2O.ai for a customer engagement engine and real-time generative AI for fraud prevention, and with Anthropic for generative AI capabilities.
    • AWS DevOps Agent: Explored for accelerating root cause analysis in cloud operations.
  • Migration Process: The data platform migration, which began in mid-2024, was completed in 9 months with HCLTech as a partner, leveraging AI and generative AI for code transformation, error checking, and 229,000 tests with 100% accuracy reconciliation. The core banking migration was an 18-month project involving partners like SAP, SAP Fioneer, Accenture, AWS, and Red Hat.
  • Regulatory Compliance: CBA worked closely with the Australian Prudential Regulation Authority (APRA) to ensure all banking data remains in Australian-based AWS facilities.

๐Ÿ”ฎ Future ImplicationsAI analysis grounded in cited sources

CBA will significantly accelerate product development and innovation velocity.
Consolidating core banking and data lake on AWS, coupled with AI-powered engineering and an AI factory, enables faster experimentation and deployment of new services.
The bank will further enhance personalized customer experiences and real-time decision-making.
With 55 million daily AI-driven decisions and 157 billion data points, the scalable cloud platform allows for more sophisticated AI models and agentic frameworks to deliver tailored services and respond to customer needs in near real-time.
CBA will continue to lead in AI adoption and responsible AI governance within the financial sector.
The bank has established an AI Factory, strategic partnerships with AI leaders (H2O.ai, Anthropic, OpenAI), and a principles-based approach to AI governance, positioning it as a top-ranked bank globally for AI maturity.

โณ Timeline

2024-07
Migration of CBA's enterprise data platform to AWS began.
2024-09
CommBank launched its AI Factory with AWS, powered by Amazon EC2 P5 Instances.
2025-02
CBA renewed its five-year strategic collaboration with AWS as its preferred cloud provider.
2025-05
CBA completed the migration of its data platform to AWS, encompassing over 10 petabytes and 61,000 data pipelines.
2025-10
CBA completed the migration of its core banking system to AWS, becoming the first major Australian retail bank to do so.
2026-05
CBA began using AI in employee surveys for workforce planning.
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Original source: iTNews Australia โ†—