Finding an edge with AI and digitalization starts with your strategy. Leon Saunders Calvert, Head of M&A and Capital Raising Propositions at Refinitiv, explores.
- A new generation of business-savvy digital heads are driving business use-cases for AI.
- Strategy comes first: If you can’t identify your digital use-cases, no AI solution can help you.
- AI tools can support the bottom line and top line. But understanding data is the key.
The volume of interest and participation in our recent webinar on ‘Using AI to drive competitive advantage in investment banking’ would have been remarkable just a few short years ago — such is the pace at which the M&A and capital-raising business is pursuing technology as a business driver.
We are seeing this in our own interaction with banks. In-house technologists have become much more influential in their organizations, not to mention proactive in purchasing of data and tools. The backdrop to this is that ‘information technology’ has moved from a support function to mission-critical and essential for future-proofing the business.
The latest webinar in our #IBDigitalization series explores the key challenges that banks are facing today and the role of AI in M&A and Capital Raising.
Even more recently, we have begun to see new roles being created within the business rather than the IT side. These are typically ‘Heads of Digitalization’ — individuals who are not necessarily technologists themselves but are very smart and laser-focused about what they want technology to do.
This has been a game-changing development for Refinitiv, which has long seen its role as making a connection with the data scientists, who can present possibilities, and with the business heads that understand an organization’s specific priorities. This is essential, because while the promise of AI is huge, what it won’t do is your thinking for you.
That might sound odd — if artificial intelligence isn’t going to think for us, what will it do? In this sense, AI is a misnomer.
It’s more helpful to think of AI as (very sophisticated) pattern recognition. This can be incredibly powerful, but it is a means to an end. So the first step must always be identifying your strategy and use-cases, as specifically as possible. AI tools can help you solve problems, but it will never be able to tell you which problems are worth solving, or in what order.
The reality of AI is much more about augmenting smart humans, with all their ingenuity and creativity, with smart tools that can intelligently weave together disparate data-sets, identify correlations and, based on this, deliver actionable insights.
If developing a digital strategy to deploy AI seems daunting, there are some common themes across the M&A and capital raising industry where AI is expected to make a big difference.
The first is in regulation and compliance, where AI tools could be used to support process around financial crime, fraud detection, sanctions screening and so on.
Another is around the productivity and efficiency of bankers. Does it really make sense having junior bankers spending so long on modeling and creating pitch books? On top of that, since the global financial crisis, the growth of the internet giants has seen serious competition for the best talent coming from outside the financial services sector. Using technology to make the working life of junior bankers more about insight and judgement will help in both attracting and retaining staff.
But AI is not just about efficiency. The really exciting opportunities lie in growing the top line through the use of predictive tools to, for example, help to originate new deals or identify business risks.
Data, data, data
If AI is the engine, then data is the fuel. The challenge here is very often not a lack of content. All banks will have an enormous amount of internal data and external data. The AI challenge is driving upwards the signal to noise ratio in order to reap value from it.
The first challenge is how do banks get the external data that they receive from third-parties such as Refinitiv, and co-mingle this with internal data on their own customers? Connecting disparate data sets from different sources, both structured and unstructured, and getting them to talk, is a major challenge.
It is also one of the reasons why Refinitiv has partnered with Squirro, a world-leader in generating actionable insights from other impenetrable data. This is critical. It is very difficult for AI tools to be applied effectively to fragmented data sources, structured or otherwise, if you can’t create some level of consistency and normalization.
The raison d’être for Refinitiv is to support our customers on their journey over the coming years, and to accelerate the development and adoption of applications that will be useful to the capital raising industry.
That is why our flagship desktop product, Eikon, is open for developers to link to and build upon. With our long history of content provision, we see the AI opportunity as a huge potential win-win, and the more brains we can bring in to the mix — organic and artificial — the better for us all.
Investment banking is in the midst of a technological transformation. Find out how our partnership with Squirro can help you gain a competitive edge.
Join the conversation in our #IBDigitalization webinar series
We are pleased to invite you to view our on-demand #IBDigitalization webinar. In this webinar, Sam Chadwick, Director of Strategy in Innovation and Blockchain at Refinitiv, and James Giancotti, CEO, Oddup, discuss cryptocurrencies and the rise of blockchain.