If you're an enterprise organization, especially in a highly regulated sector, you understand the struggle to innovate and drive change while maintaining your security and compliance posture. In particular, your banking customers' expectations and needs are changing, and there is a broad move away from traditional branch and ATM-based services towards digital engagement. With this shift, customers now expect personalized product offerings and services tailored to their needs. To achieve this, a broad spectrum of analytics and machine learning (ML) capabilities are required. With security and compliance at the top of financial service customers' agendas, being able to rapidly innovate and stay secure is essential.

Amazon is set to open up the machine-learning algorithms that power its recommendations and forecasts to Amazon Web Services customers in a bid to make it easier to adopt the new technology. The AWS annual Re:Invent conference in Las Vegas also saw the introduction of new tools to help companies manage their data, improve their security and introduce blockchain services. In a keynote speech that referenced Fortnite, the Beatles, Elvis Presley, the Clash and Queen, chief executive Andy Jassy announced a total of 20 new products and services that it would allow its customers to use the company's smart technology to get started in machine learning, making it easier for its customers to get started and customise the new technology to meet their needs. "We're entering this golden age of what's going to be possible," he said. "The problem with machine learning today is it's still pretty early for most companies in terms of knowing what they want to do with machine learning and having the people to build and tune the models.That's why you see us spending so much time, energy and investment and so many releases in machine learning and AI in the past couple of years."

"Mandy Monroe" works relentlessly to reach out to customers of Lee Kia of Greenville in North Carolina to schedule service appointments. A consistent revenue generator, Mandy doesn't complain, gossip, make personal phone calls on company time or pop chewing gum. Mandy doesn't even take bathroom breaks. That's because Mandy is a cyberstaffer driven by artificial intelligence. The virtual assistant, created by the software provider Conversica, conducts email conversations with dealership service customers.

UK bank, Royal Bank of Scotland (RBS) has announced it will be rolling out an artificial intelligence programme called "Luvo" to support its human staff. Using artificial intelligence is not a new idea in financial services, with intelligent financial instruments being used to manage money on a daily basis, but Luvo is different in that it has been given a "human" personality. The idea behind this decision is to make the AI seem more personable, friendly and warm. At present, it is being used to help support human employees but the bank hopes to roll out the tech so that customers can interact with it directly. It is currently being used to answer basic queries like "my customer has lost their bank card, what steps do I need to take now?", which is rather banal, but as the tech develops it is likely to offer more in the future.

The ability to engage service customers--and keep them engaged--is critical to a dealership's revenue and, more importantly, its ability to retain those customers through to the next buying cycle. And that buying cycle is worth a lot more than just one or two cars; according to dealership executive and author Carl Sewell, every customer is worth 517,000 over his or her lifetime. NADA's December 2015 stats report that, although the average new car sale yielded 3.58% gross, the average service yielded 72%. But contacting and engaging service customers takes time, effort, and close monitoring, and that's just not possible for the typical service team when there are hundreds or thousands of customers to work. Not surprisingly, good opportunities get dropped.