BBVA Partners with AWS to Put AI and Data Technologies at the Heart of Its Business

Spanish bank BBVA has announced its plans to put artificial intelligence and data technologies at the heart of its business strategy. BBVA intends to leverage these technologies to enhance internal processes, risk management, growth, and customer-facing services. To support these efforts, BBVA has partnered with Amazon Web Services (AWS) to utilize cloud-based machine learning and analytics.

BBVA’s strategy is to put AI and data technologies at the heart of its business

BBVA is looking to harness the power of artificial intelligence and data technologies to improve all aspects of its business. The bank believes that the use of these technologies will enable it to deliver more personalized and effective services to its customers, while also reducing costs and improving efficiency in all of its operations. BBVA’s global head of data engineering, Ricardo Oliver, sees this partnership with AWS as a significant milestone in the bank’s efforts to become a more data-driven organization.

The use of cloud-based machine learning and analytics from Amazon Web Services supports this strategy

To support BBVA’s strategy, the bank has turned to Amazon Web Services to utilize its cloud-based machine learning and analytics tools. These tools will enable BBVA to build predictive analytics applications that can analyze vast amounts of data to identify trends, predict customer behavior, and make more informed decisions. With these tools, BBVA will be able to create a more comprehensive understanding of its customers’ needs and preferences in real time.

Plans for a new data platform are a significant milestone for BBVA

As part of its partnership with AWS, BBVA plans to build a new data platform that will serve as a secure repository of all its operational and customer data. This new platform will be built using AWS Lake Formation and Data Zone tools that can build, manage, and secure the data. By creating this platform, BBVA will have access to a centralized source of data that can be analyzed more efficiently, allowing the bank to make better decisions and provide more personalized services to its customers.

The AWS Lake Formation and DataZone are tools for building, managing, and securing a data platform

BBVA has chosen to use AWS Lake Formation and DataZone tools to build, manage, and secure its new data platform. The AWS Lake Formation is a collection of services and tools that can help organizations build and manage data lakes, while DataZone is an AWS security and compliance tool. By utilizing these tools, BBVA can ensure that its data is secure and complies with all financial services regulations.

The role of over 1,000 data scientists in BBVA’s AI Factory is to build, train, and deploy machine learning models

BBVA has more than 1,000 data scientists in its AI Factory who will play a vital role in the bank’s data-driven strategy. These data scientists will use Amazon Sagemaker to build, train, and deploy machine learning models for predictive analytics applications. Thanks to these machine learning models and the massive amount of data that BBVA will have access to, the bank will be able to deliver more personalized and effective services to its customers.

BBVA has an existing relationship with AWS to manage data as part of its digital transformation journey

BBVA already has an existing relationship with AWS in managing data for its digital transformation journey. The bank’s investment banking unit uses AWS cloud technology and services from market information provider Bloomberg to build a platform known as BBVA C-Fit, which traders use to manage data directly. This platform demonstrates how BBVA has already been utilizing AWS technology to become a more data-driven organization.

Widespread AI investments in banks span from customer interactions to investment banking strategies

BBVA’s efforts to put AI and data technologies at the heart of its business strategy are not unique. Banks across the world are now spending heavily on AI, with investments ranging from customer interactions at consumer-facing units to supporting investment banking strategies. These efforts highlight the importance of AI and data technologies in the banking industry and demonstrate how these technologies can help banks become more competitive and efficient.

Transparency issues exist in the reporting policies for responsible AI among European banks

While there is no denying the benefits of AI and data technologies in the banking industry, there are still concerns about the responsible use of these technologies. A recent study by Evident found that European banks were the least transparent when it came to reporting their policies for responsible AI. This finding highlights the need for banks like BBVA to be transparent about their use of AI and data technologies and to ensure that they use these technologies in a responsible and ethical manner.

BBVA’s partnership with AWS to put AI and data technologies at the heart of its business strategy is a significant milestone for the bank and the banking industry as a whole. By leveraging these technologies, BBVA can deliver more personalized and effective services to its customers while also reducing costs and improving efficiency in all its operations. However, it is important for banks to be transparent about their use of AI and data technologies and to ensure that they use these technologies in a responsible and ethical way.

Explore more

Mimesis Data Anonymization – Review

The relentless acceleration of data-driven decision-making has forced a critical confrontation between the demand for high-fidelity information and the absolute necessity of individual privacy. Within this friction point, Mimesis has emerged as a specialized open-source framework designed to bridge the gap between usability and compliance. Unlike traditional masking tools that merely obscure existing values, this library utilizes a provider-based architecture

The Future of Data Engineering: Key Trends and Challenges for 2026

The contemporary digital landscape has fundamentally rewritten the operational handbook for data professionals, shifting the focus from peripheral maintenance to the very core of organizational survival and innovation. Data engineering has underwent a radical transformation, maturing from a traditional back-end support function into a central pillar of corporate strategy and technological progress. In the current environment, the landscape is defined

Trend Analysis: Immersive E-commerce Solutions

The tactile world of home decor is undergoing a profound metamorphosis as high-definition digital interfaces replace the traditional showroom experience with startling precision. This shift signifies more than a mere move to online sales; it represents a fundamental merging of artisanal craftsmanship with the immediate accessibility of the digital age. By analyzing recent market shifts and the technological overhaul at

Trend Analysis: AI-Native 6G Network Innovation

The global telecommunications landscape is currently undergoing a radical metamorphosis as the industry pivots from the raw throughput of 5G toward the cognitive depth of an intelligent 6G fabric. This transition represents a departure from viewing connectivity as a mere utility, moving instead toward a sophisticated paradigm where the network itself acts as a sentient product. As the digital economy

Data Science Jobs Set to Surge as AI Redefines the Field

The contemporary labor market is witnessing a remarkable transformation as data science professionals secure their positions as the primary architects of the modern digital economy while commanding significant wage increases. Recent payroll analysis reveals that the median age within this specialized field sits at thirty-nine years, contrasting with the broader national workforce median of forty-two. This demographic reality indicates a