We're already used to unlocking a phone by simply placing it in front of our face and accessing certain apps using fingerprint technology. Behind these advances is biometrics, identification technology based on recognising each person's unique physical characteristics: their fingerprint, their face and their voice. Voice is already the gateway to many services and applications that have become an integral part of our daily lives. The level of intuitiveness and user-friendliness enabled by voice-based interfaces place them heads and shoulders above other options when it comes to interacting in a seamless way with our devices. From a biometrics standpoint, voice offers additional benefits.

On many occasions, the greatest impediments to creating Artificial Intelligence solutions do not lie in the capacity of highly qualified teams, but in establishing an effective way of working between the different professional profiles involved in the life cycle of analytical models. This is one of the main tasks we are currently tackling at BBVA AI Factory. It is a task guided by three concepts: simplify, accelerate and reuse. My first direct contact with the AI Factory was in April 2020, in the middle of lockdown. I found myself with a team of data scientists who were extremely competent in creating AI models, but who needed to continue to push for common working guidelines in order to deal with the complexity – both organisational and technical – that exists in the Engineering domain.

Your financial health has improved since last month. Would you like to know by how much?" Blue, BBVA's new virtual assistant (VA), is the one doing the talking. Blue is integrated in the bank's mobile banking app in Spain (for Android and iOS) and can respond to over 100 user requests from the more than 800 features available in the application. Blue is pleasant, patient, and able to put itself in the shoes of others. It loves talking to humans and is always willing and ready to help customers. And it wants to learn lots of things in order to become even more insightful. These are just some of the personality traits that characterize BBVA's new voice assistant, which came to life out of a complex process that factored even the most minor details. The IT consulting firm, Gartner, defines virtual assistants as tools that help users perform a series of tasks that previously required human assistance. VAs use predictive models, natural language processing tools, recommendation engines, personalization systems based on artificial intelligence and advanced data analytics to do their job: assisting users and automating tasks. "VAs listen to and observe behaviors, build and maintain data models, and predict and recommend actions," the consulting firm explains. Blue's artificial intelligence capabilities are the result of a hybrid development: made up mostly of parts created by BBVA and others based on technologies that were readily available on the market and benefit from an advanced level of maturity, such as natural language processing (NLP) techniques. Specifically, the core of the system's artificial intelligence functionality is a 100 percent BBVA in-house development called Lenny. It is based on a set of cloud-based microservices and is responsible for orchestrating all the pieces that go into making Blue work. Thanks to this BBVA-developed'artificial brain', Blue is connected to the application functionalities that are powered by advanced data analytics. Examples include predicted banking transactions and financial health features, which the BBVA virtual assistant makes readily available to the customers by using natural, human-like dialog. "During the development of Blue, one of the most significant challenges was ensuring that we could cover the full range of functionality that BBVA, as a major player, offers in its app -- recognized as the most complete on the market -- in a voice and text-based virtual assistant," Eliseo Catalán, Head of BBVA Spain's Smart Assistants explains. Achieving this required that all the features in the app -- offered thanks to BBVA's digital capabilities -- were correctly set up and that each use case was thoroughly trained so that the user is given the appropriate response at every juncture of the customer journey. "We do all of this for the various platforms that might have different capabilities.

New technologies have been a real revolution in the banking sector. Techniques such as natural language processing, automated learning and automation software are already used within the financial sector. The role technology plays in people's lives –both personal and business– is continually growing. As a bank, BBVA committed to transforming itself digitally long before the start of the last decade, understanding that technology was going to have a huge impact on how the industry operates. In this article, BBVA experts in various fields give their view on the changes that 2020 will see in the technological landscape.

The toolkit, which is free to access, is aimed at business leaders to help companies make informed decisions about AI solutions that protect the customer and shareholders alike. Artificial intelligence and big data, are proven contributors of innovation to the financial system. The digital explosion and technological advances have caused a revolution in society and in the corporate organization. As explained by Jorge Sicilia, Chief Economist of BBVA Group and director of BBVA Research, the financial sector is no stranger to these changes and the next wave of innovation is going to be based on artificial intelligence. With the global spend on AI expected to hit $52 billion in the next three years, according to the WEF report, and to double the annual growth rates of major economies in the next 15 years, the kit is also aimed at ensuring business can benefit from machine learning in the best way.

Machine learning uses large volumes of data to make predictions about what will occur in the future, based on patterns extracted from past examples. However, a higher or lower degree of certainty always exists for each of these predictions, and this certainty can decrease when the data being used is especially complex. Machines' current ability to learn is present in many aspects of everyday life. Machine learning is behind the recommendations for movies we receive on digital platforms, virtual assistants' ability to recognize speech, or self-driving cars' ability to see the road. But its origin as a branch of artificial intelligence dates began several decades ago.

The agreement establishing Intel as BBVA's priority partner is part of a series of strategic, global alliances that the Group is formalizing with tech leaders. The goal is to become a more flexible and scalable bank, capable of offering its clients the best data-driven digital services. Automatic learning is a prerequisite for intelligent systems. It enables data-driven predictions and creates new business opportunities. Banking in general, and BBVA in particular, is already taking advantage of this technology in order to improve products and services for its customers.

Systems capable of identifying exoplanets, algorithms to boost efficiency in network deployment operations, automatic translation tools or virtual assistants capable of recommending content. AI promises to bring a virtually limitless range of applications to organizations, and these are just some of the ones that Google and Telefónica are exploring through the use of machine learning techniques. Ricardo Martin Manjón was named as BBVA Global Head of Data in April this year, having previously been the bank's Global Head of Data Strategy and Data Science Innovation. His role sees him lead the bank's development, deployment and future thinking around how BBVA drives forward its use of data throughout the Group, so it can achieve its strategic objective of bringing the age of opportunity to everyone. In this interview Martin Manjón outlines why BBVA has a strategic focus on data, how that manifests itself across the entire group, what it will mean for customers in the future and the critical importance scale plays in data management.

Greta Thunberg is 16 and lives in Sweden. Until February last year, she was just another student concerned about the environment. Today, she's become the world's most influential climate activists, after founding'Fridays for Future', a movement that encourages school students to take time off from class to participate in demonstrations against their countries' governments for breaching environmental laws. Greta believes that we're heading towards a natural disaster and the planet's destruction if we fail to change our habits as a society. And that includes everyone, from large industries to the individual citizen.

Propel Venture Partners, BBVA's San Francisco based venture capital investment vehicle, has co-led the latest funding round into a business seeking to link up psychology and machine learning. The $5.2 million in Series A funding round into London-based AI start-up DataSine will help business launch a new platform, which combines expertise in psychology and machine learning to help smaller businesses personalize their marketing at scale. DataSine's content personalization platform Pomegranate is a collaborative AI-powered campaign platform that tailors content to personality specific to the customer. Pomegranate helps businesses tailor content to resonate with their audience, from the segment level down to the individual. It applies machine learning to behavioural data that companies already collect to build customer profiles, and provides an AI-powered content editing platform to guide marketers in tailoring a range of content elements, including words and images.