Client

Our client is an Indian multinational bank and financial services company. It offers a wide range of banking products and financial services for corporate and retail customers through a variety of delivery channels and specialized subsidiaries in the areas of investment banking, life, non-life insurance, venture capital, and asset management.

Challenges

• Build scalable architecture to handle banks increasing data volumes and real-time needs 
• Siloed data and need to integrate structured and unstructured data, bringing a 360 view of analytical records across various banking LOBs for AI-based decision making 
• Incomplete support for building AI use cases with the existing platform
•  Data governance for all data sets on the cloud 
• Compliance and risk management

LTM Solution

• Built on open source and open standards one Data Platform- Databricks Delta Lakehouse leveraging Azure Cloud platform for complete and accurate downstream Analytics for thousands of business users, building 300+ uses cases leveraging ML flow improving customer experience
• Performed Data ingestion, ETL compute on billions of financial transactions data across retail, corporate, SMEG, wealth banking, and leveraged both streaming data as well as years of historical data needed for aggregations and compliance
• Databricks Lakehouse architecture helped the bank build a 360 view of customers, transactions, prospects, risk, branch, and profitability across Retail, NRI, Wealth, Corporate, Risk, Finance, Sales, and Marketing LOBs
• Analytics-based prospecting, propensity models, collections, and pre-delinquency management
• Built customer-level models for optimized decision-making

Business Benefits

• 20% Reduction in IT Infrastructure cost by leveraging Databricks compute resources
• 2X Delta Lakes Performance improvement as compared to Vertica
• 5X Reduction in ETL time
• 2X Faster time-to-market