One subject never fails to light up the eyes of senior bankers and regulators when they're questioned about their efforts to end the money laundering-related scandals that have spread across northern Europe over the last two years: technology. There can be no more damning indictment of the integrity of a bank, or its host nation, than the public revelation that a licensed institution is being used as a laundromat for ill-gotten gains. And what is more enlivening for money-laundering supervisors and bank-compliance officers than showing your firm and country is at the forefront of a technology that could make these troubles disappear? Some of the biggest actors in Europe's financial sector are converts. The UK's Financial Conduct Authority is particularly enthusiastic about using technology to fight money laundering.

Lenders in the U.S. overwhelmingly plan to expand financing activity this year. According to new research from Magilla Loans, which offers an anonymous search engine data for both home and business loans, a survey of mortgage and business lenders found plans to originate more than half a trillion dollars' worth of loans in 2018. According to the report, 88 percent of lenders plan to lend more in 2018 than they did in 2017, and more than a third (36 percent) said they plan to lessen requirements for loan approval. While the data included business loans, Magilla noted that mortgages are the main driver behind this trend. So while lending volume in the U.S. might be expanding, gaps in business finance – especially among SMBs – remain.

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.

Marco, what can we do about AI? Marco, are we doing enough on AI?" The questions all come from senior executives, desperate to harness the potential that AI promises. Yet Bressan is bemused by how the technology is talked about at board level and in the media. "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." At the most rudimentary level, AI involves teaching machines to learn and to interact in order to undertake cognitive tasks that were usually performed by humans. The type of AI featured in sci-fi films in which machines possess a human-like intelligence, sometimes referred to as general artificial intelligence, remains a distant and elusive prospect. The most optimistic experts, such as Google's director of engineering, Ray Kurzweil, predict that AI will be able to outsmart humans by 2029. Conservative predictions expect this to take at least 100 years, if at all. Of more immediate relevance to those working in financial services is the deployment of narrow artificial intelligence. These applications undertake specific tasks using problem solving, deduction, reasoning and natural language processing. Such programmes are being applied across financial services, from the development of customer service programmes that use natural language processing to manage and field customer queries, through to programmes that can conduct financial research and make sophisticated models of financial markets to identify trading opportunities. The potential for narrow applications has led to a boom in AI investment. Technology companies are undoubtedly leading the way. In 2015 the giants of AI – Microsoft, Google and Facebook – spent 8.5 billion on AI research, acquisitions and talent. In comparison, financial institutions have made a cautious foray into the field. A handful are making investments by hiring high-level data scientists or acquiring AI companies. The hedge fund Bridgewater Associates hired the former chief engineer behind IBM's Watson supercomputer. BlackRock has also been busy hiring some high-profile names and has announced a joint venture with Google to explore how to use AI to improve investment decision-making. Goldman Sachs has invested in a number of promising AI start-ups, including the financial research platform Kensho. Yet most financial institutions have been slow to adopt AI, even though it is likely to usher in a new type of bank, with data and technology as its heart. Failure to adapt may lead to extinction for some. As Neil Dwane, global strategist at Allianz Global Investors, explains: "Technological competence is absolutely essential for at least staying in the game.

In transaction banking, the focus on technological development has centred on the possibilities of blockchain technology. However, this has overshadowed the arrival of AI into transaction-banking platforms. AI and machine learning are helping to further reduce manual checks and processes. The first target for implementation is sanctions and compliance. As companies become increasingly international, irrespective of size, checking against sanctions has become an essential activity for more than just the MNCs. AI can learn through experience what can pass through the sanctions filter, and what compliance obligations need to be checked.