BBVA has rolled out a machine learning operations (MLOps) system in partnership with Amazon Web Services (AWS). This new setup integrates directly into the bank’s comprehensive ADA platform, which serves as its unified global hub for data and artificial intelligence capabilities. The initiative aims to significantly speed up the entire process of creating, testing, and launching AI-powered tools throughout the organization.
By combining expertise from both organizations, the architecture streamlines how data teams handle the full lifecycle of machine learning models.
It introduces greater automation for routine procedures and quality checks while embedding these workflows seamlessly into BBVA’s existing technology infrastructure.
The solution was showcased at the recent AWS Summit, highlighting its potential to transform how financial institutions scale artificial intelligence.
One of the standout benefits is enhanced independence for development groups.
With over 6,500 professionals using the ADA environment—including roughly 1,000 dedicated data scientists—the new framework allows teams to build and release solutions more quickly across different business areas.
Early trials focusing on tailored client suggestions and economic projections demonstrated dramatic improvements: development timelines shrank by 20 to 75 percent, while operational expenses for computing resources dropped between 40 and 55 percent.
A core element of the design involves robust oversight mechanisms built into every stage of model creation.
Automated checks ensure proper validation, full documentation, and compliance monitoring, allowing models to move safely from experimentation to live use without compromising the bank’s internal review standards.
This is particularly important in banking, where regulatory demands for accountability, data protection, and risk management are exceptionally high.
The system also preserves a complete record of activities, supporting transparency and audit requirements.
The architecture leverages Amazon SageMaker AI services extensively.
A significant advancement is the use of temporary, on-demand computing spaces that teams can spin up for parallel experimentation.
Developers can test new ideas simultaneously without disrupting shared resources. Once work concludes, these environments shut down automatically, conserving costs and accelerating iteration cycles.
Natalia Sampietro, a leader in BBVA’s Data & Analytics Enablement group, emphasized the strategic importance: artificial intelligence delivers maximum impact only when deployed at industrial scale across an entire enterprise.
This MLOps layer provides a clear edge by hastening internal process modernization and enabling the rollout of a range of explainable AI features for customers.
Carlos Alegre Berges, AWS’s global account lead for BBVA, acknowledged the collaboration.
He noted that the project empowers thousands of data experts to innovate with both speed and discipline.
The partnership underscores BBVA’s forward-thinking approach to responsible, large-scale AI adoption worldwide.
The joint effort gained visibility at the AWS Madrid Summit, where organizers also released a report on AI opportunities in Spain.
The BBVA case stands out as a key example of how established companies can harness cloud technologies to drive meaningful digital progress in competitive sectors.
This development reflects BBVA’s ongoing commitment to leveraging cutting-edge cloud and AI tools. By addressing key bottlenecks in model governance and infrastructure efficiency, the banking platform now strategically positions itself to deliver more personalized, timely services while maintaining the highest standards of security and compliance.