In general, businesses use the customer data they access for internal purposes, creating value-added services. Yet, there is greater potential for society as a whole beyond corporate “closed doors.” Public-private sector collaboration using data sources for external initiatives can produce significant benefits. For example, a door could be open that would facilitate the use of data to help fulfill the United Nations 17 Sustainable Development Goals (SDGs).
“The SDGs are nothing more than KPIs for social development, and all KPIs have to be measured, their performance tracked over time, because that is how they will indicate if we are on the right path or not when it comes to spreading opportunities and prosperity, especially among the most disadvantaged,” explains Juan Murillo, Head of Analytic Outreach in BBVA's Data Strategy and Data Science Innovation department, during his presentation at Big data to Action 2019, held in Madrid.
According to Murillo, the role of big data in the non-profit areas “is the same as in a corporate environment: using data helps to chart a course, supported with knowledge and a vision of the route, and of the obstacles that we might find in the path.” He mentioned, however, that "it is unfortunate, but vulnerable groups are the least likely to leave a digital fingerprint, which constrains data initiatives for the common good."
There are still barriers to data collaboration that need to be overcome. Among the things needed, Murillo mentioned the need for an effective inter-industry data source transfer mechanism, an initiative that is backed by the European Commission. He emphasized that BBVA has been a leader in this area, sharing its anonymous and aggregated data sources. "This should be the trend: companies sharing the enormous value that lies in their data in order to spread prosperity." Other obstacles include: the reliability of data, something that can be resolved by applying traditional statistical techniques like sampling to the massive data sources; the perception that businesses need to be incented to participate in these kinds of external initiatives; and finally, moving from a proof of concept to making a true positive impact.
Juan Murillo, durante su participación en el ‘Big data to Action 2019’.
Using data for the common good: the BBVA example
BBVA has a long history of collaborating with public organizations in order to reap social value from data, always on anonymized sources of data and always protecting its customers’ privacy.
Among other examples, Murillo explained the collaborative process between BBVA and the United Nations, as part of its Global Pulse initiative, in order to “explore data’s descriptive capacity to improve our ability to react to natural disasters.” He explained that this collaboration also serves to measure how data analysis can contribute to the attainment of the United Nations Sustainable Development Goals.
How? By analyzing credit card payment and ATM withdrawal data, BBVA, in collaboration with the United Nations, was able to uncover tendencies that occur during a natural disaster; for example, how people get ready for such an event, the approach and speed of recovery. It was also possible to identify new metrics that could proves useful in the event that a similar disaster occurs. Specifically, BBVA analyzed Hurricane Odile, which had significant economic impact on the peninsula of Baja California in 2014.
"We are extremely concerned for the privacy of our customers, which is why the source data never left BBVA’s infrastructure and were analyzed by data scientists in the bank, who provided responses to the questions posed by the United Nations’ team. What was shared externally were the results based on aggregate data and visualizations that provided a summarized view of various conclusions in a single interactive tool.” Murillo stated.
But BBVA’s initiatives go beyond Hurricane Odile. For example, BBVA used these data sources to work hand in hand with Mexico’s Department of Tourism to help the government better understand the dynamics related to tourism and apply them to its “Magical Towns Program.”
The project, Urban Discovery, provides another example that demonstrates open data in action: the BBVA Data & Analytics team, alongside the CARTO team examined how three large cities – Madrid, Barcelona, and Mexico City – are subdivided into functional zones. On the one hand, by analyzing movements based on the digital trail left by credit card payments, it was possible to establish links between different urban areas, the first step to then understanding the relationship between the two areas. On the other hand, these sources were used to identify and describe the specialties of the different urban areas of the cities analyzed, which can serve as a guide to identify, for example, areas in different cities that share so much in common they might be considered “urban area twins”, information that can then be used to help make decisions about commercial expansion in the area.
Professionalizing Big Data
Juan Murillo also referenced the development of Big Data as a field in Spain. Specifically, he explained that "when BBVA began working in this area, back in 2011, there was a huge shortage of profiles, because data science was still a new discipline, a hybrid between statistics and computer science, and it was still not regulated." However, in recent years, universities have responded to the private sector demands for talent in the field and have programs to train these new professionals.
"At BBVA we've covered the odds: on one hand, we have made efforts to offer internal training, skilling up the talented analysts who are already part of our teams; and on the other hand, we recruit new talent with these skills through our Young Professionals Data initiative," he concluded.