It is Not About Deep Learning, But Learning How to Represent

Juan Arévalo

d&a blog

Recently, we setup a workgroup dedicated to Deep Learning (DL). Workgroups offer opportunities to share internally ideas, concepts, resources, code, etc. Additionally, they are meant to promote the use of Machine Learning at BBVA. I remember vividly how José Antonio Rodríguez, one of the impellers of this workgroup, told us back then: “We should call it the workgroup on representation …

Presentation of Urban Discovery: Our Contribution to an Improved Vision of Big Cities

Beatriz Alonso

d&a blog

Last September 21st, at BBVA Innovation Center, we presented the results of our last research on territorial analytics: Urban Discovery, a new tool developed together with CARTO, that shows how the analytics of anonymized credit card data can serve to identify functional areas in Madrid, Barcelona and Mexico City, to describe city main dynamics and areas of specialization, and to …

A Cost-Effective and Scalable Collaborative Filtering based Recommender System

Ivan Fernández, César Silgo and Juan Arévalo

d&a blog

Last 26th of September we had the opportunity to present a collaboration between BBVA Data & Analytics and BEEVA at the Theatre of Partners during the AWS Summit Madrid 2017. In the conference, we presented a cost-effective approach for collaborative filtering based Recommender Systems (RS), that scales to millions of users and a million products. Our implementation made use of …

What we saw at Spark Summit 2017: Spark embraces Deep Learning

Mauricio Ciprian

d&a blog

Spark Summit 2017, which took place in San Francisco in June, brought together more than 3,000 data scientists, developers and industry experts that participated in more than 170 to discuss recent developments and future trends that will shape the future of the data industry. This is the biggest worldwide event of the Apache Spark community, the technology that has become …

Rediscovering Cities through Credit Card Data (Part 2)

Juan Murillo

d&a blog

— Results interpretation from an urban perspective Project Background In a previous paper we outlined the methodology, models, and tools used for the analytical and graphical representation of the Urban Discovery project that we developed together with CARTO. In this second part, the focus is on the functionality of the results in order to interpret and improve the administration of …

Rediscovering Cities through Credit Card Data (Part 1)

Juan de Dios Romero

d&a blog

— Analytical and Technological Process Administrative municipal boundaries, such as districts and neighbourhoods, are currently used not only to rule cities but also to describe the behaviour of their citizens. In fact, official statistics and open data are published using these divisions. However they may not be the best option for none of these purposes; nowadays, people and businesses? expand …

Improving Customer Experience with Forecasting Models

Mauricio Ciprian

d&a blog

Direct debit and credit cards have made the lives of many easier. They have allowed us to save time and headaches, and helped us finance goods that exceed our monthly purchasing power. Sometimes, they have also created situations when an unforeseen payments came through in an unexpected moment with a low balance the missing payment involves a penalty. To solve …

What we saw at RecSys 2017 Conference

Marco Creatura

d&a blog

RecSys, which took place in Como last 27th August 2017, is one of the largest academic conferences on Recommender Systems (RecSys) and has reached this year its eleventh edition with an all time record of attendees (627), proving the rising importance of Recommender Systems in the current digital agenda. At BBVA Data & Analytics, we believe that Recommender Systems can …

Learning from Cardiac Arrhythmias to Improve Customer Satisfaction — Working with Imbalanced Data

Felipe Alonso-Atienza

d&a blog

Background Customer satisfaction is a complex indicator. It can change after every interaction, can be influenced by external factors, and can lead to multiple outcomes. Cumulative dissatisfaction can lead the customer to terminate the relationship with the service provider and yet, it is difficult to measure with traditional methods like customer satisfaction surveys. Machine Learning algorithms offer today the possibility …

Our Reading List about Machine Learning for Designers

Fabien Girardin and Alejandro Vidal

d&a blog

At BBVA Data & Analytics, we continuously collaborate with design teams at BBVA to create user experiences that rely on machine learning techniques (e.g. predictive models, recommender systems). We documented that interdisciplinary practice in Experience Design in the Machine Learning Era that then led to a contribution in collaboration with Neal Lathia from Skyscanner at the AAAI 2017 Spring Symposia …