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Not Big Data - it's the right-sized data that counts
The frenzy of big data is settling down. Companies that want to be ahead of the technological curve are now focusing on the most sophisticated ways of applying this data for their own benefit and their clients. It is this ability to break down the data provided by machine learning which is such a sought after competitive advantage.
At Lombard Odier, finding the best way to crunch data and offer solutions to clients has been an ongoing quest for over 15 years. "Our own technology engine, G1, was first developed in 2002 and the next generation, G2, powers My LO, our wealth monitoring platform," says Oliver Hart, senior private banker, Lombard Odier (Europe) S.A.
Allowing clients to select their own 'right-sized data' is at the core of My LO, whether looking at their portfolio by asset class or generating customised reports. The bank considers it one of its finest assets. Hart names it “one of the most compelling, competitive edges a private bank can have".
Such has been the success of the G1 engine and its successors that they are now being used by other banks, renting the technology from Lombard Odier.
This shows that technology spend on AI (artificial intelligence), when done right, is not a drag on a P&L (profit & loss) statement. Instead, according to Hart, the engine is now a profit center for Lombard Odier, allowing its staff to focus on other areas.
Sponsoring the UK Tech Awards
This vision led Lombard Odier to take an interest in how AI is disrupting other sectors and ultimately to us sponsoring a category in the UK Tech Awards, with the “Best Use of Tech in the Digital Economy Award" being a natural fit.
“I set off to understand what the premier award which recognizes technology achievements was. From corporate finance experts to tech entrepreneurs, their responses all led me to the UK Tech Awards, which is a great showcase of the best of tech," says Hart. “All the candidates (in this category) are trying to solve inefficiencies and make the world a better place."
Many of the UK Tech Award candidates this year, such as Deliveroo or Revolut, have applied the breaking down of big data or machine learning to solve fundamental challenges in their industries, be it food delivery or finance.
One strong example this year came from Revolut, which turned card fraud detection on its head by launching its own machine learning technology to detect compliance-related crimes - faster and with better pattern detection than any human eye. From March to July 2018, it saw a 30% drop in those crimes.
What's next for AI?
One concept lies at the heart of many current corporate applications of machine learning: Next Best Action (NBA). This technology works by an algorithm being fed a stream of data, such as customer behaviour or purchasing trends, among many types of potential business interactions. It then interprets these to provide a company with the best type of action to take at any given time to maximise the chances of a sale or engagement with a customer.
Deliveroo's real-time dispatch algorithm chooses the right rider for each deliver via a system which it clams can predict the best overall outcome for a food delivery. The algorithm, named Frank, works in several ways. It considers the menus of around 10,000 restaurants available through the company's app, the peak times for meal orders across different locations and traffic conditions over time. Able to cope with millions of simultaneous orders, it instructs riders on which paths to take and can predict at what time restaurants should start preparing a specific order.
In finance, the same ideas can be applied to understand a client's future needs to guide investment decisions by wealth managers. Tom Brakke, a leading consultant for asset managers and advisory firms, points out how the rise of AI has changed the skillsets advisors need to have.
“For those researching securities or investment managers, big data and AI won't eliminate the need for old-fashioned investigative research and analysis, but the capabilities should be looked at as potential levers to make their activities more productive and targeted," he says.
Brakke has high hopes that the application of big data seen so far will continue to improve. “I believe that most organisations are very early in the process of thinking about how to make adjustments, if they have started at all. Over time, I hope this will result in more unique solutions for their clients. Much of the computerisation to date has led to generic applications that are broadly offered rather than tailored," he said.
Looking past the bottom line
However, according to Roger Gorman, CEO and founder of ProFinda, companies are about to take on the next leap forward in the use of AI - how it can be used to transform the way companies are organised. ProFinda uses AI to help clients get the most out of their global workforce. It provides management with a map of the talents in their pool of staff, making it easier to create teams filled with the best people for a specific project.
"The application of AI today is at a very simple level. The value of AI is to remove the drudgery of work," he says . "Many companies are still married to their old structures and ways of doing things on ancient systems. The transition is not easy but it is a matter of time."
This year's UK Tech Awards nominees seem to be mastering this transition. They serve as shining examples of British companies ably using AI and machine learning to more efficiently serve customers, improve their bottom line or even crack down on crime.
Important information
This document is issued by Bank Lombard Odier & Co Ltd or an entity of the Group (hereinafter “Lombard Odier”). It is not intended for distribution, publication, or use in any jurisdiction where such distribution, publication, or use would be unlawful, nor is it aimed at any person or entity to whom it would be unlawful to address such a document. This document was not prepared by the Financial Research Department of Lombard Odier.
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