Finance organisations are increasingly turning to artificial intelligence in pursuit of competitive advantage. However, although many firms are achieving successful results from AI projects, scaling up enterprise-wide often remains elusive. Rob Smith, CTO of award-winning cloud services provider Creative ITC, explains how the growing trend of as-a-Service IT models is accelerating digital transformation across the finance sector and enabling IT leaders to unlock greater ROI. Uptake of artificial intelligence (AI) and machine learning (ML) is continuing to rise as financial organisations progress their digital transformation plans. These new technologies offer banking and finance firms new ways to accelerate and improve decision-making and customer service.

If you thought taking a few machine learning courses on Udemy might be enough to inure you against future unemployment then yesterday's report on machine learning in financial services from the Bank of England and Financial Conduct Authority (FCA) will come as a bit of a shock. The report is based on a survey of 106 banks and finance firms in London. It turns out that, yes, machine learning is being used in banks. But, no, it's not hard to find anyone to fill the roles and that this is the least of the worries as machine learning is rolled out across the finance sector. The charts below, from the report, show where machine learning (ML) is already most in use in the banking sector (defined as building societies, international banks, retail banks, UK deposit takers, and wholesale banks) and in the investments and capital markets sector (defined as alternatives, corporate finance firms, fund managers, principal trading firms, wealth managers and stockbrokers, and wholesale brokers.)

Technological efficiencies will result in the biggest reduction in headcount across the U.S. banking industry in its history, with an estimated 200,000 job cuts over the next decade, Wells Fargo & Co. said in a report. The $150 billion annually that the country's finance firms are spending on tech -- more than any other industry -- will lead to lower costs, with employee compensation accounting for half of all bank expenses, said Mike Mayo, a senior analyst at Wells Fargo Securities LLC. Back office, bank branch, call center and corporate employees are being cut by about a fifth to a third, with jobs related to tech, sales, advising and consulting less affected, according to the study. "It will be a dramatic change in contact centers, and these are both internal and external," Michael Tang, a Deloitte partner who leads the consulting firm's global financial-services innovation practice, said in an interview in the Wells Fargo report. "We're already seeing signs of it with chatbots, and some people don't even know that they're chatting with an A.I. engine because they're just answering questions."

In today's rapidly growing digital age, long-term survival and success are increasingly being linked with how "smart" a business can be. And for financial services firms that means using technology to become more intelligent, and processes and systems that talk to each other and learn from one another. Banks, insurers and wealth managers are pouring billions of dollars into artificial intelligence (AI), machine learning and other types of technologies that are already not only raising productivity levels, but reducing risk and actually creating new jobs. According to Accenture research, the financial services industry is now the third most impacted by productivity gains achieved with the implementation of AI, behind only the media and telecoms, and manufacturing sectors. The figures show that by 2035 its use should have resulted in an increase of US$1.2 trillion in gross value added, which measures the output value of all goods and services in a sector.

Just because one Goldman Sachs MD quit banking for an elusive residency at Google Brain, don't assume you need to leave finance to pursue your passion for machine learning. As artificial intelligence (AI) comes of age, there are a growing number of firms putting self-teaching computers to work in financial services. Better still, most of them are hiring. These are the top companies in the finance world for machine learning right now, along with who they like to hire and the vacancies they have open. If you're interested in machine learning, you may want to apply soon – universities globally are currently training-up thousands of machine learning specialists, including several savvy former traders who saw this trend coming.