BBVA apply influence of emotions on digital ads with Oracle

BBVA improved the customer experience and campaign success using data science from Oracle Machine Learning within Cloud Infrastructure.


Our goal in embedding behavioral economics in the bank’s culture is to make life easier for our customers and give them a first-class experience. Oracle Machine Learning supports this goal, helping us build a brand new way of doing business based on understanding the cognitive processes behind decision-making.

Álvaro GaviñoBehavioral Economics Global Leader, BBVA

Business challenges

Banco Bilbao Vizcaya Argentaria (BBVA) is a Spanish multinational financial services company based in Madrid and Bilbao. It is one of the largest financial institutions in the world, with operations predominantly in Spain, North and South America, and in Turkey. As of June 2020, BBVA's assets amounted to €753 billion, with 7,700 branches, 125,000 employees, and 79 million customers in more than 30 countries.

Defining itself as ‘the digital bank of the 21st century,’ BBVA positions technology at the forefront of all activities. In doing so, sales of digital products have been growing year on year, with a 66% increase registered in the second quarter of 2020.

Although being a leader in e-banking solutions, BBVA needed to improve customer experience, finding itself hampered by traditional marketing methods and internal constraints. To address these issues, in 2017, BBVA created a Behavioral Economics group in charge of better understanding human motivation and providing more personalized and relevant messaging.

Launching a new initiative, the bank’s Client Solutions unit collaborated with Oracle Consulting to develop Behavioral Economics Learning Algorithm (BELA), a system based on Oracle Machine Learning, Oracle Transaction Processing, and Oracle Cloud Infrastructure.

The objective of this solution is to identify the cognitive mechanisms that are most relevant when generating a marketing campaign for different targets, using advanced analytics and machine learning algorithms.

Based on this learning, the system generates variants of an advertisement to incorporate specific cognitive mechanisms into the text, for each audience group, using Natural Language Processing techniques.

The generation of copys and the automatic publication of the campaigns, bring a significant reduction of effort and time to deliver to the Digital Marketing teams.

Using Oracle Visual Builder, a cloud-based software to develop, collaborate on, and deploy applications within Oracle Cloud, users have applications with an intuitive graphical interface that guides them through the entire process of defining and publishing campaigns.

Within three years, sponsored by the bank’s President and the Board, BELA has become the global platform for proposing innovative financial solutions to its customers.

Why BBVA Chose Oracle

BBVA selected Oracle for its robust market position, as well as for the technical expertise and business understanding demonstrated by Oracle Consulting that helped build a groundbreaking solution.

“Oracle Consulting fully understood the business requirement. They were able to provide us with a turnkey end-to-end solution including a front-end portal,” said Álvaro Gaviño. “It’s given us a new way of doing business through a system that would have required monumental in-house efforts and light years to get up and running. With Oracle Machine Learning we are doing a far more complex job in much less time thanks to artificial intelligence.”


Based on several dozen algorithms within Oracle Machine Learning, the Behavioral Economics group rolled out a new way of doing business using artificial intelligence applied to Digital Marketing.

BELA helped to break down cognitive barriers and boost the appeal of customer value propositions. In Colombia, for example, too much online information was causing cognitive overload and browse abandon. By rectifying the wording and visuals of the offer, BBVA Colombia saw a huge uptake in applications for credit cards and online banking accounts. “One of our objectives is to be more relevant to our clients by offering them products and services that really capture their specific interests,” said Álvaro Gaviño, Behavioral Economics Global Leader at BBVA.

Furthermore, across geographies, marketing campaigns generated through machine learning produced a 30% to 40% improvement in click-through and conversion rates compared to content created by traditional methods.

BBVA’s marketing teams now enjoy more autonomy and control. Creatives that took days or weeks for agencies to work on are now finalized in a matter of minutes and published directly in Google Ads through API interfaces.

BELA has replaced pre-testing that was based on time-consuming random trials or opinion polls. By using natural language programming, the systems itself suggests now the optimum campaign content per target segment and mobile device and auto-evaluates the probable results.

Along with faster campaign creation and deployment, machine learning also helped the bank to achieve micro-segmentation and hyper-personalization of email and banner ads. In addition, BELA generates multiple versions of messaging to match the more granular target segments. “With Oracle Machine Learning we are doing a far more complex job in much less time thanks to the ability to easily increase the volume of marketing campaign versions and personalized micro-segments,” said Álvaro Gaviño.

Beyond the definition of algorithms and templates by BBVA’s central group in Madrid, Client Solutions has harnessed the scalability of Oracle Cloud Infrastructure for sharing BELA with teams in Colombia, Peru, and Mexico to cater for regionalized financial health campaigns and initiatives.

Machine Learning and Behavioral Economics are now incorporated into the bank’s Talent and Culture division best practices.

Published:January 19, 2021