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Facing the data-driven future

Facing the data-driven future

6 March 2019 | 7 min read

Day three of Innotribe at Sibos 2018 Sydney

What role will financial services play in an AI-permeated world?

Innovation first changes processes, then business models and life choices. Across the financial services industry, artificial intelligence (AI) is enhancing existing workflows, executing tasks quicker, better, cheaper. This will help to deliver a better user experience today and even tomorrow, but what about the day after? Will today’s financial services even be relevant? 

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SWIFT Innotribe - Sibos 2018 Day 3 wrapup

“To prepare for the future, understand that AI will permeate everything,” said Dr Eng Lim Goh, Chief Technology Officer, Hewlett Packard Enterprise, presenting Wednesday’s Innotribe session, ‘Advanced machine intelligence’.. But how do we prepare for that AI-permeated future? More specifically, how do we as financial service providers leverage AI to the best advantage of our customers - and our staff - in a new and unpredictable environment? These AI-dedicated sessions prompted as many questions as they answered - andthat’s actually a very good sign. If AI enables machines to engage in an open-ended process of learning, evolving, adapting, we must continue to do the same, or risk redundancy. 


We have to not only think strategically, but tactically too, addressing the practical issues. “Focus on data,” advised Goh. “Data will decide how smart your machines will be. There’s no point in having the data if you don’t curate it. Curate and federate your data now!” This, perhaps, was the first key insight of the day: the scientists may be making the machines, and giving them the capacity to learn, but we all have the opportunity to contribute to their intelligence and understanding through data. We can, in effect, design AI to be what we want it to be, and our data is the tool at hand. We can, make AI-driven machines into bankers;we can raise them in our own image.

Destination unknown?

The significant practical issue is not how to do this. We already have big data, and we have ‘narrow AI’, i.e. single-task, problem-solving machine learning. With this, we have already begun the learning process needed not only to master AI, but also to turn it to our own purposes. Undoubtedly, ‘how’ needs more work, but there is a more pressing issue. It’s one that relates as much to the future path of the financial sector – the direction that AI and other innovation will enable it to take – as to the technology itself. In short, what kind of financial services do we want AI to deliver?

First, the vision. In the AI-enabled future, machines learn, and they teach each other. We trust them enough to give them independence and agency. They act for us, and their actions are as effective and appropriate as allowed by the quality of the data, instructions, principles and parameters we have provided. So far, so good, and so soon. Such independent AI may be entering the banking industry within the next decade, Goh suggested. Their decision-making abilities will also be enhanced by real-time access to data; they will be transparent; oversight will be automatic.


This all sounds very positive. But here’s the truly pressing issue: there is no point in training an artificially-intelligent workforce if the customers don’t like, want or need what we’re offering. In the future, AI will permeate the lives of individuals, families, businesses and societies, changing the every day, for everybody (and, via the Internet of Things, everything). Innotribe 2018 not only encouraged us to ask where AI would fit into the financial services industry of the future, but where financial services would fit into the AI-enabled future.

Sharing the experience 

In Innotribe’s flagship ‘Future of Money’ session, we learned that selling financial products is reaching obsolescence. “We no longer think about buying products, but about consuming experiences,” said moderator Udayan Goyal, co-founder, Apis Partners. The possession of data is no longer the starting point in a process of working out what product the customer might want – or realise that they needs – next; it is the means of access to a commercial ecosystem built around Goyal’s concept of “experience consumption”. How do you fit banking into an experience? 


The recurring analogy here is that customers don’t buy mortgages; they buy houses. The mortgage transaction is embedded in the house purchase; the desired experience – delivered in part by the bank – is the move to a new neighbourhood. As mortgage-providers, we get our share of credit for securing the big garden and the beautiful view, as well as for the loan approval, but the overall experience rests on collaboration between many parties. In the era of experience consumption, traditional service providers need to partner more closely with other firms, not least with the tech companies that hold vast amounts of data on their customers, which could be a source of wisdom for our AI programmes. In this context, open banking is just another term from data-driven collaboration in pursuit a superior customer experience.

Putting trust to the test 

What is the industry’s bargaining position vis-à-vis, say, the tech giants? Data usage is not without controversy and is increasingly subject to legislation. Banks have the significant advantage in that they are used to operating in a highly-regulated environment. In a prospective collaboration, a tech company may have more data, but a bank’s regulated status gives it value as a trusted data-holding partner. This provides incentives for collaboration today. But over a ten-year horizon, given that a bank is a point of trust in a complex and fast-evolving commercial environment, the opportunity goes beyond simple collaboration. On Wednesday afternoon, Innotribe delegates heard one description of the future from Neal Cross, Chief Innovation Officer, DBS, who outlined the thinking behind his bank’s launch of “the world’s largest API platform”. It’s out there, Cross said, and it’s good for business. “We can have thousands of companies helping to make us successful,” Cross continued.

Across the financial services spectrum, AI is taking hold. But in the main it is currently executing tasks quicker and better than humans, handling simple customer queries, reaching credit decisions, making investment recommendations. Even though this is still ‘narrow AI’, it raises important ethical questions, due partly to the inferences that AI systems may draw from their data on us. As new business models, customer needs and service propositions emerge, trust will need to be maintained, both in technology and institutions. 


“The AI has to be trusted,” said Dr Heike Riel, Director of IoT technology and AI solutions, IBM Research, in an aptly-titled Sensemaker session, ‘The Interconnectedness of Everything and Advanced AI’. “It’s all about you, your data, your privacy,” continued Riel. 

As we begin to use fast-evolving opportunities and tools to fit banking into a world permeated by AI, the question of trust will be critical to continued relevance. Banks have been in the trust business for centuries, learning that it is hard won, and harder to regain. Equally, we all know that the past is no guarantee of future performance. Whether you’re focusing on the tactical or the strategic challenges, join us throughout 2019 as Innotribe reflects the next phases of the industry’s AI conversation.



Session wrapup and interviews 

Follow our participants

Uday Goyal

Tony Fish

Neal Cross

Dr Eng Lim Goh

Brett King

Clara Durodie

Diana Paredes

Richard Harris