Tailoring credit products to the diverse needs of customers
HDFC Bank's Credit Risk Analytics and Innovation department migrated from a 16-node Hadoop cluster to the Databricks Data + AI Platform on Azure, using Delta Lake and Unity Catalog to power fraud control, marketing optimization and credit risk model building, significantly reducing query time and accelerating data pipelines for downstream risk management.
Overview
HDFC Bank's Credit Risk Analytics and Innovation department migrated from a 16-node Hadoop cluster to the Databricks Data + AI Platform on Azure, using Delta Lake and Unity Catalog to power fraud control, marketing optimization and credit risk model building, significantly reducing query time and accelerating data pipelines for downstream risk management.
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Inspect the highlighted sourceThe challenge
HDFC Bank's CRAIN department faced a 16-node Hadoop cluster that lacked the computing resources, automation and scalability required, making campaign-specific legacy ETL jobs costly and resource-intensive to develop, execute and maintain, and slowing the team's ability to focus on innovations that better serve customers.
The solution
The CRAIN department at HDFC Bank migrated to the Databricks Data + AI Platform on Azure, transferring on-premises data to the cloud via a secure VPN, with batch transfers moving data into Delta Lake as the department's primary data repository.
Reported business value
By leveraging Databricks ETL, analytics and AI/ML capabilities, the bank can now scale data ingestion cost-effectively, powering business use cases including deriving actionable insights to improve fraud control, optimizing marketing campaigns and refining credit risk model building and deployment.
Sources
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