Switzerland's largest banks radically improves customer profiling by centralizing data and enabling advanced real-time analytics
~3,650High-income clients acquired
~19Months ROI
$15M+Solution-driven revenue growth
“After automation of our data pipelines, we significantly reduced manual effort and operating costs while ensuring accuracy of crypto.”
Romain Braud
Head of Digital Assets
Challenge
A leading Swiss private bank needed to unify fragmented crypto market data, news feeds, and real-time updates into a single reliable data foundation — while meeting strict scalability, consistency, and low-latency requirements to power advanced customer analytics and machine learning applications.
Solutions
Built a scalable data warehouse on AWS and Databricks to aggregate, process, and store both structured and unstructured data from multiple external sources.
Established automated real-time data pipelines ensuring continuous, consistent, and up-to-date data availability across the platform.
Created a structured, ML-ready data layer to support downstream analytics, customer profiling, and machine learning applications.
Delivered the system through iterative sprints with full QA and DevOps support, ensuring reliability and performance from day one.
Outcome
The bank gained a reliable, automated data foundation that replaced manual operations with real-time pipelines — enabling advanced customer profiling, crypto analytics, and ML-driven insights that directly contributed to acquiring ~3,650 high-income clients and $15M+ in solution-driven revenue growth.
