Case Study: MONETA Money Bank achieves 2/3 reduction in operational costs and 2x faster ML-driven innovation with Databricks

Bring banking into the 21st century with data and ML

Moneta, the Czech Republic’s fourth-largest bank with over 1 million customers and a reputation for innovation, needed to modernize its analytics as data volumes ballooned. Their legacy on‑premises systems couldn’t scale to process terabytes of data from multiple channels, slowing time‑to‑insight and tying up data engineers in cluster management while the bank pursued real‑time recommendations and fraud detection.

By adopting the Databricks unified data analytics platform on AWS, Moneta gained a fully managed, scalable environment with automated cluster management, Delta Lake and MLflow, and collaborative notebooks supporting SQL, Scala, Python and R. The change streamlined data engineering, accelerated ML from prototype to production by 2x, cut operational costs by two‑thirds, and improved cross‑team productivity while enabling real‑time personalization and stronger fraud detection.

MONETA Money Bank

Jakub Masek

Lead Data Engineer