Case Study: Credit Suisse accelerates AI-driven innovation and scales data with Databricks

Modernizing financial services with data and AI

Credit Suisse set out to modernize its legacy, relationship‑based banking model, which was constrained by on‑premises systems, manual processes, privacy and scale challenges, and limited access to only market and pricing data. These limitations slowed product development and prevented the firm from embedding machine learning and AI across the business to meet rising customer expectations.

The bank standardized on a cloud‑based analytics platform using Azure Databricks and MLflow (Delta Lake, data science, ML, ETL) to provision scalable clusters, ingest diverse internal and third‑party data (including alternative and ESG data) and accelerate experimentation and model deployment. The change enabled rapid prototyping and production ML, powering real‑time recommendations, anomaly detection and transaction enrichment, improving operational efficiency, enabling new products and expanding global market reach.

Credit Suisse

Anurag Sehgal

Managing Director, Head of Global Markets