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AI set to transform investment banking

Sofia Spencer
Sofia Spencer, Head of Digital for Investment Banking, Refinitiv

Investment Banking is experiencing a technology transformation. Sofia Spencer, Proposition Manager, M&A and Capital Raising at Refinitiv, explores how digitalization is changing the M&A and capital raising space and brings you the highlights from our latest webcast with Squirro on the topic.  


  1. Refinitiv and Squirro recently hosted a webcast to explore how AI can be used to drive competitive advantage in investment banking
  2. The competitive dynamics in investment banking will be fundamentally altered by AI: it will become as pervasive and indispensable as the internet.
  3. AI augments human ingenuity — so take people on the journey.

Artificial intelligence is not the answer to everything, but in a hyper-competitive market place like investment banking, where smart people go head-to-head every day, smart tools can change the game — in terms of productivity gains, lead generation capabilities and customer experience.

The potential impact of AI is difficult pin down because its uses are potentially infinite. On a recent Refinitiv #IBDigitalization webcast that I had the pleasure to host, my guest Dorian Selz, CEO of Squirro, asserted that no part of investment banking operations will be unaffected, from deal sourcing and risk modelling, through to automating execution in equity and debt capital markets, and across the middle and back office area.

Sofia Spencer Quote. AI set to transform investment banking

Implementing AI as part of a digitalization strategy

By deploying AI tools, as well as new technologies that automate the banker’s workflow, incremental efficiencies can build rapidly.

In short, the full range of processes in investment banks will be affected by machine learning and AI. The question then is how to sensibly implement AI as part of a coherent digitalization strategy?

The first step is to identify your strategy and zero-in on use cases — something my colleague Leon Saunders Calvert discusses in a blog on the topic. In the first instance, consider questions such as: Are you concerned with the top or bottom line? Does your use case imply a small incrementhttps://www.refinitiv.com/perspectives/ai-digitalization/ai-competitive-advantage-investment-banking/al improvement, or a reimagining of an entire process?

Whatever happens, you will need to take others on a journey because the value of AI is how it augments and complements, rather than replaces, people.

AI set to transform investment banking

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.

Data co-mingling

Another big question is how to make sense of your customer data and how to co-mingle third-party data from providers such as Refinitiv, and allow them to ‘talk’.

Only a very small proportion of data held within investment banks is used for decision-making. This is largely because of the difficulties of processing unstructured data — whether news articles, research notes, client presentations, meeting minutes and so on — and capitalizing on it for business advantages.

There is little that existing staff can do about this on their own. After all, investment bankers are already bombarded with data. Cognitive technology can handle disparate, fragmented and unstructured content sets and provide actionable insights by stitching these together and creating connections. In this way, the potential that could be unlocked by AI is difficult to exaggerate.

Investment banks are looking to technology for help in creating M&A prediction models, enhance due diligence processes and to automate parts of the workflow.

Predictive analytics and M&A targets

For instance, at Refinitiv, we have found that when it comes to predictive analytics for identifying M&A targets — in addition to the traditional transaction and company data — information from our M&A deals database can be a powerful training data set. Above all, we’ve seen that the easiest way to improve your predictive algorithm is to fundamentally improve the quality of data.

Ultimately, AI can help validate hypotheses and identify patterns that otherwise would be difficult to detect, allowing you to make cognitive leaps by correlating large and disparate data sets — a salutary warning against being overly-prescriptive around the use of content.

Speaking to one of our customers recently, they utilised the prospect of how driverless cars has prompted questions for the caffeinated beverage industry, because so much coffee is consumed to help keep drivers awake. AI could help validate and uncover whether the correlation is indeed genuine.

The possibilities of AI are huge, and in our experience, investment banks are increasingly keen to discover its potential. Over time, it seems likely that, just as the internet invented entirely new business models and made others redundant, AI will do the same across many sectors, including investment banking. Like all innovations, it therefore poses threat and opportunity.

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Investment Banking is in the midst of a technological transformation. Find out how our new 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 attend our upcoming #IBDigitalization webinar November 20th.  In this webinar, Sam Chadwick, Director of strategy in innovation and blockchain at Refinitiv, and James Giancotti, CEO, Oddup, will be discussing cryptocurrencies and the rise of blockchain.

AI set to transform investment banking