Case Study: CaixaBank achieves 12% higher loan profits and saves 60,000 hours with Oracle Machine Learning

CaixaBank boosts potential with Oracle Machine Learning

CaixaBank, a leader in Spain’s retail banking with over 5,000 branches and 9,000 ATMs, faced the twin challenges of digital disruption and growing volumes of heterogeneous data. To stay competitive against all-digital entrants and meet regulatory and security requirements, the bank needed a scalable, unified analytics platform to consolidate data from commercial, retail and internal sources and to accelerate machine learning and AI use across the organization.

CaixaBank implemented Oracle Machine Learning together with Oracle Advanced Analytics, Oracle Data Mining and Oracle Analytics on Oracle Cloud Infrastructure, running models where the data lives and supporting SQL and R for faster deployment. The initiative improved loan-risk model accuracy by 7%, driving a 12% increase in loan profits, and produced a direct-debit algorithm with 99% accuracy that replaced manual checks and saved about 60,000 human hours—freeing staff for advisory and revenue-generating activities while positioning the bank for future digital and regulatory changes.

CaixaBank

Xavier Gonzalez

Farran Director of Big Data Analytical Tools