The Monthly Briefing

A new step on our way



Introducing
BBVA AI Factory SL
🎉

We are proud to say that today we take a new step on a journey that began a decade ago.

BBVA Data & Analytics SL, one of the cornerstones of the bank’s transformation around data, becomes BBVA AI Factory SL. The new company incorporates the analytical talent of BBVA Data & Analytics and maintains its values and principles, which will continue to shape our character and our way of doing things. In addition, the entity adds the expertise of Madiva Soluciones in product creation and the technical capabilities of Data Engineering necessary to achieve our objectives.

It was 2011 when a group of inquiring minds at BBVA created a small innovation program to explore opportunities to exploit financial data. This team was the seed of BBVA Data & Analytics SL. In these ten years, we have supported the bank's digital transformation, understood the business needs and helped clarify the type of solutions that Artificial Intelligence can bring to a financial institution such as BBVA. We have also met our colleagues from Madiva Soluciones and now we are working together with engineers and AI architects in the AI Factory.

In this article we delve into the road travelled during these ten years, and celebrate this new milestone that represents a step forward in our journey. We will also continue to share our concerns and the work we do through our communication channels, such as this digest. We keep swimming!

"A further step in the consolidation of BBVA AI Factory"

Today, BBVA AI Factory SL is incorporated as a new legal entity, and I am honoured to be writing to you as CEO. I am also very fortunate to be accompanied in this venture by our COO Marta Sanz.

We are not starting from scratch. Far from it. Now begins a new stage of this vital journey. Our mission as a company is to create data products aligned with the bank’s strategic priorities, maximising the value creation for all the businesses and countries in which BBVA operates.

I feel committed, confident and grateful. I am accompanied by a great team of people who I know, respect and admire, and who have already more than demonstrated their value, talent and human qualities. I would like to thank Elena Alfaro, Jon Ander Beracoechea, Marcelo Soria and Marco Bressan for their vision and ambition, for their vision and ambition, as well as their hard work in bringing the impact of Artificial Intelligence to the entire Group. And to Juanjo Divassón, Fernando Alfaro, Paco Gonzalez and Alejandro Ruyra for their complicity, support and ability to “think backwards”.

I am convinced that we are going to work hard during this new phase, and that we will enjoy it and learn a great deal. And that it will be a shared success.


Check out the official note and the full article written by Francisco Maturana on Linkedin (in spanish).

Data Science beyond models

In this talk (in spanish) organised by Afi Escuela de Finanzas, our colleague Juan de Dios Romero delved into how we work when building data models, especially the importance of the first phases of the work, what we know as business understanding. It is essential to dedicate time to these first phases, which are often resolved too quickly, in order to ensure that the project can correctly follow the next phases. Don't miss it!


Further reading

+DALL·E and CLIP, two new neural networks (OpenAI)
With these two neural networks, OpenAI wants to move towards the building of multimodal neural networks. DALL·E, whose name comes from the artist Salvador Dalí and the robot WALL·E, can successfully turn text into an appropriate image for a wide range of concepts expressible in natural language. The second, CLIP, has the ability to reliably perform a staggering set of visual recognition tasks. Given a set of categories expressed in language, CLIP can instantly classify an image as belonging to one of these categories in a “zero-shot” way, without the need to fine-tune on data specific to these categories, as is required with standard neural networks.

+Which are the best AI labs worldwide? (CNBC)
AI researchers hate this question, but there may be some consensus.

+What are the most important statistical ideas of the past 50 years? (Andrew Gelman and Aki Vehtari)
The authors argue that the most important statistical ideas of the past half century are: counterfactual causal inference, bootstrapping and simulation-based inference, overparameterized models and regularization, multilevel models, generic computation algorithms, adaptive decision analysis, robust inference, and exploratory data analysis. You agree?

+AI can also help find trees in the Sahara. (The Guardian)
It was a great surprise for Martin Brandt, assistant professor of geography at the University of Copenhagen, when he realized that the part of the Sahara that the study covered, roughly 10%, “where no one would expect to find many trees”, actually had “quite a few hundred million”.

+Can companies like Facebook or Twitter eliminate the effect of filter bubbles? (IEEE Spectrum)
Instead of building echo chambers, Facebook, Twitter and company can tweak their code to broaden exposure to wider ranges of views.

Quote

of the

month

"Data will need to flow securely and with the speed to support real-time analytics and decisions to be made at the edge."

Cindy Maike, VP Industry Solutions at Cloudera


In this article in Insidetelecom, Yehia El Amine writes about the rise of data management and data governance work at every any kind of company. In this sense, Cindy Maike points out that with cloud computing usage on the rise, companies will require more robust data governance programs to ensure the "data sprawl" does not happen and, if it does, that data is properly managed and governed.

We also have a new logo 😎

See you folks!


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