Neural networks training is a time consuming activity, the amount of computation needed is usually high even for today standards. There are two ways to reduce the time needed, use more powerful machines or use more machines. The first approach can be achieved using dedicated hardware like GPUs or maybe FPGAs or TPUs in the future. But it can also be done by splitting the task between more general purpose hardware like the one used in cloud systems. This document summarizes the conclusions reached after researching the use of distributed neural networks.

For the AI competition, BBVA had more than a hundred entries from 26 different countries. Themes ranged from providing more personalised products and services, better risk management, offering customers greater insights into their transaction, personalised money management systems and real-time AI chatbots. Commenting on the winner, BBVA's Head of Open Talent Marisol Menéndez said: "The judges agreed unanimously on our winner, although it was a hard decision as all ten of our finalists have build exceptional products. "AI really has the potential to be a game-changer for the financial service sector, offering both customers, clients and business huge opportunities to deliver better, faster, more individual, more accurate and more insightful products and services – and that why at BBVA we wanted to run a competition based on this specific issue. "Change was selected because their solutions is really at the heart of what we are trying to do with technology as a bank – to use it to reduce people's stress and support them with their financial decisions making. "Being able to hold the final here at Money 2020 has been fantastic – not only has it given our finalists the chance to meet and share their ideas with potential customers and partners, but we've also help all of them get some valuable exposure for their business.

The revolution in customer services will come in the form of chatbots. These robots are able to converse with customers and, according to Cross, will increase the functionality of mobile banking exponentially: "If, for example, you want to know how much you have spent on coffee during the month, you can download an Excel sheet that will give you the amount. However, you can also ask a chatbot, "How much have I spent on coffee this month', and it will give you the answer." Artificial intelligence will also develop new functionalities in other areas of concern to banks such as money laundering, legal issues, and fraud detection. Artificial intelligence is in fact already being used for legal tasks.

Artificial intelligence could increase South America's gross domestic product (GDP) growth by at least one percentage point annually by 2035, according to Accenture Research's report How artificial intelligence can accelerate South America's growth. The report calls attention to this technology's potential to transform the region's labor market and create a new relationship between humans and computers. In Brazil, for example, the study noted that the so-called gross value added (GVA) could increase by a total of $432 billion in this 17.5 year period. In terms of banks, the study reports that seven in ten bank users trust the financial guidance provided by automated systems. Some 39% of users consider the use of robo advisor platforms an agile tool and 31% see it as a way to lower costs for both banks and their customers.

AI is a core focus for BBVA and for many banks around the world. The reason for this is simple: automating tasks, adding insight, processing information and managing data can increasingly be done faster and more efficiently by machines. This is not to denigrate the impact of human interaction, rather that we can empower people – whether customers or colleagues – to do more if we use the power of computing to help them make decisions or understand information. BBVA already has examples of AI in usage today – for example our MIA chatbot service our Garanti customers in Turkey enjoy – and we'll be rolling out more in the coming months and years. But how do we design future AI products and services – often years in advance – and what are the scenarios we are looking at.

Artificial intelligence (AI) made the leap from science fiction to the corporate world some time ago. Amazon and Netflix use it routinely to make purchasing recommendations, iPhone users speak to Siri every day, and banks give investment advice or calculate risks thanks to these technologies. But these are only the first hesitant steps of AI, which is due to have a major impact on the financial sector, as revealed in this report in the magazine Euromoney, and featuring an interview with Marco Bressan, Chief Data Scientist at BBVA. Artificial Intelligence has been present in the financial industry for many years now, Marco Bressan, Chief Data Scientist at BBVA, tells Euromoney: "Currently it denotes a vision of the future; an aspect of the sci-fi imagination; something that you still can't do. But the truth is senior financial executives have been doing AI-related work, research and deployment of products for years", he notes. When we talk about Artificial Intelligence we refer to a set of technologies –many created decades ago– rather than one single product or system.