Bring banking into the 21st century with data and ML
Reduction in operational costs
team productivity through cross-team collaboration
Faster time-to-market of new features
With over 1 million customers, Moneta is the 4th biggest bank in the Czech Republic and has repeatedly been recognized as the country’s most innovative bank. The Databricks Data Intelligence Platform enables them to leverage data and advanced analytics to innovate the customer experience with use cases ranging from real-time recommendations to fraud detection.
Massive data volumes cripple legacy systems
As banks today collect more and more data across all their channels, Moneta found that their legacy analytical systems weren’t able to deal with the increase in data volumes. Moneta started a digital mission to improve their customer experiences with use cases such as real-time recommendations and fraud detection. Due to the massive volume of data at scale, it was challenging to move forward for Moneta to achieve their goals.
Processing terabytes of data across all digital channels, making it extremely challenging to handle the large amount of data they had.
Their on-premises solutions struggled to scale operations to support data science efforts against all of this data coming from various data sources at different speeds. As a result, time-to-insight was slower than they required to drive innovation.
Data engineering spent too much time configuring clusters and maintaining infrastructure. This slowed data flow to the data science team for machine learning and analytics.
Simplified data engineering unlocks ML innovations
With the Databricks Data Intelligence Platform, Moneta can now tackle their big data and AI problems with a simple, scalable and secure managed service on AWS. It fosters a scalable and collaborative environment across data science and engineering, allowing data teams to more quickly innovate and deliver ML-powered innovations that feed into their services and products.
Production ready and out-of-box solution for critical workloads.
Fully managed platform with automated cluster management simplifies the infrastructure and operations at any scale.
Collaborative notebook environment with support for multiple languages (SQL, Scala, Python, R) enables a diverse team of users to work together in their preferred language.
Improving the banking experience with data and ML
With Databricks, Moneta has been able to harness the insights within their various streams of data to create innovative technologies that keep the world moving.
Improved operational efficiency: Features such as auto-scaling clusters and support for Delta Lake and MLflow has unified analytics operations from data ingest to managing the entire machine learning lifecycle, cutting operational costs by two thirds.
Better cross-team collaboration: Shared notebook environment with support for multiple languages has improved team productivity.
Faster time-to-insight: Databricks has improved time-to-market, allowing them to accelerate prototype to production by 2X.
