Sold by: phData
Our Open Intelligence Architecture for the banking industry is an AI-native, consulting-led solution from phData that helps banks modernize fragmented data estates into a unified, AI-ready cloud platform across AWS, Snowflake, and/or Databricks. By combining open table formats on Amazon S3 (Apache Iceberg) with a governed intelligence layer and FinOps-first design, it enables real-time risk, fraud, and customer intelligence while reducing total cost of ownership.
Overview
Banking Open Intelligence Architecture on AWS is purpose-built for banks that need to consolidate siloed core, risk, finance, and channel data into a unified, governed, and interoperable Intelligence Platform. phData brings more than a decade of experience in financial services, helping leading banks modernize trading, credit, and finance systems while navigating strict regulatory, liquidity, and operational risk requirements. This offering is delivered as a natively with AI as the authors and our experts validating what goes to production.
The architecture leverages Amazon S3 Tables as the open, interoperable storage layer, with services such as AWS Glue, Amazon EMR, and AWS Lake Formation used for ingesting, transforming, and governing high-volume “bronze/silver” workloads from core banking, payments, and ledger systems. Advanced analytics and AI/ML workloads are executed on Snowflake and/or Databricks deployed on AWS, where phData designs semantic layer and governed data models to power regulatory reporting (e.g., BCBS 239-style data aggregation, stress testing), fraud and AML models, and customer 360 analytics. By decoupling storage from compute and standardizing on open formats, banks gain flexibility to run workloads on the right engine for risk, finance, and customer domains while avoiding vendor lock-in and improving data residency and lineage controls.
For AI and agentic use cases, the Open Intelligence Architecure allows for workloads to be conducted across Amazon Bedrock and Bedrock AgentCore, Snowflake Cortex, Databricks Genie, or any combination of the three, enabling use cases such as real-time credit risk assistants, fraud investigation copilots, and self-service insights for treasury and finance teams, all grounded in governed data with clear observability and FinOps guardrails. Throughout the engagement, phData applies a proven FinOps methodology to baseline platform spend, shift low-value workloads off premium compute, and reinvest savings into higher-impact AI capabilities and applications for banking.
Highlights
- Modernize banking data platforms on AWS with an open, FinOps-first architecture using Amazon S3, Apache Iceberg, Snowflake, and Databricks to unify risk, finance, and customer data.
- Power AI-driven banking use cases from credit and liquidity risk to fraud detection and customer intelligence with an architecture flexible enough to support AI workloads on AWS, Snowflake, and Databricks.
- Regulatory-grade governance and observability reporting, data lineage, and cost transparency by decoupling storage from compute and applying a proven FinOps framework tailored to banking workloads on AWS.
Details
Sold by
Delivery method
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Pricing
Custom pricing options
Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Support
Vendor support
Software associated with this service
By Databricks, Inc.
The Databricks Data Intelligence Platform unlocks the power of data and AI for your entire organization. Enjoy up to $400 in usage credits during your 14-day free trial. Cancel anytime. After your trial ends, you will automatically be enrolled into a Databricks pay-as-you-go plan.