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Since 2014, BBVA has transformed its approach to data monetization, evolving from basic internal analytics to a robust strategy that leverages data science across the entire organization. With over 50 data scientists in its dedicated subsidiary, BBVA Data & Analytics (D&A), the bank has established modern capabilities, including a data lake and a suite of reusable algorithms.
BBVA, a global financial group, began its data monetization journey by establishing a data science center of excellence in 2014. By 2017, it had significantly enhanced its data monetization portfolio by improving existing activities, exploring new approaches, and investing in numerous projects. BBVA defines data monetization as converting data into financial returns through three main strategies: selling information solutions, improving business processes, and enhancing core offerings with analytics.
With over 132,000 employees and €691 billion in assets by 2018, BBVA operates in over 30 countries and has been recognized for its digital capabilities. The establishment of a Chief Data Office in 2017 aimed to integrate data-driven activities across the organization.
Prior to 2014, BBVA focused on internal operational improvements using traditional analytics. The evolution included partnerships with institutions like the MIT Senseable City Lab, leading to innovative analytics applications, such as visualizing urban spending patterns.
Overall, BBVA's strategic focus on data monetization has positioned it as a leader in the financial sector, providing valuable insights for other organizations on similar journeys.
Chief Data Office Establishment:
In late 2017, BBVA created a Chief Data Office reporting to the CEO, aiming to embed data-driven practices throughout the enterprise.
Center of Excellence:
In 2014, D&A was formed to foster innovation in financial big data, separate from the main bank to attract talent and navigate regulatory landscapes.
Talent Management:
D&A implemented a unique hiring and retention strategy, focusing on employee development through self-guided training programs, which contributed to a low attrition rate.
Collaborative Projects:
Data scientists were co-located with project teams across the bank, promoting collaboration and ensuring that real business challenges were addressed.
BBVA's monetization efforts focus on three primary areas:
Selling Information Solutions:
D&A aimed to self-fund through external information solutions, collaborating on social-good projects to build credibility and market understanding.
Improving Business Operations:
By applying advanced analytics, D&A identified inefficiencies in core processes, generating significant cost savings and optimizing operations.
Enhancing Product Features:
Analytics were integrated into core banking products, such as a personal finance tool that gained widespread adoption among users.
BBVA’s data initiatives have fostered a culture of experimentation and innovation, enabling teams to adopt data-driven decision-making. The bank's efforts have yielded substantial economic benefits, with a structured framework to evaluate the impact of data projects on revenue and operational efficiency.
By balancing various project types, BBVA ensures a sustainable portfolio that supports its broader digital transformation goals, demonstrating the significant potential of data monetization in modern banking.
Resources: https://sci-hub.se/downloads/2019-09-16/93/alfaro2019.pdf
Book Reference
For a deeper understanding, refer to Data is Everybody’s Business: The Fundamentals of Data Monetization by Barbara Wixom, Cynthia Beath, and Leslie Owens.
