The digitalization of investment banking has created new opportunities, from the automation of workflows to using AI to find hidden M&A opportunities. Leon Saunders Calvert, Global Head of M&A & Capital Raising, explores the latest trends.
- Investment banks are looking to technology for help in creating M&A prediction models, deal origination ideas or to enhance the automation of workflows.
- Our technology is supporting clients through an open platform, with our Labs also on hand to help generate deal-related insights.
- The webinar “Using AI to predict opportunity in M&A” is the first in a series of events looking at the digitalization of investment banking.
The fundamental promise of digitalization for most capital raising and M&A professionals is the use of intelligent computing power to make more sense of the world and derive profitable insights from it.
But many prosaic challenges stand in the way of implementing such an ambition. These include:
- Finding out how to provide non-technological front-line staff with the tools to access this processing power, and to derive actionable insights from disparate, fragmented and unstructured content.
- How to automate deal making processes and workflow to improve the efficiency of originating and executing transactions.
- How to pass on these benefits to the corporate clients of investment banks — the acquirers, sellers and issuers themselves — to demonstrate increased value creation in the services the advisors offer.
We believe a number of tactics are emerging that address some of these capital markets-specific challenges from the digitalization of investment banking.
Deal origination ideas
By co-mingling proprietary content, concerning a bank’s clients for instance, with alternative sources of data from third parties, and then stitching these together using AI tools to create connections, investment banks can help drive deal origination ideas.
In this way, institutions can extract ever more value from their CRM systems.
Others are making use of technology to create deal prediction models that identify the most likely M&A or IPO targets.
There is equally a huge focus on the automation of workflow, that will free up advisors’ time so they are able to provide genuine advice rather than manage processes and manually compute financial models.
Perhaps further down the line, distributed ledger technology will begin to drive new forms of capital raising through the issuance of new securities over the blockchain and the potential to create governance tools and liquidity regarding non-listed securities.
Open platform approach
We have been at the forefront of the information business for more than a century, so we feel a responsibility as much as an opportunity to provide our clients with the means with which to augment their proprietary information and truly exploit this emerging opportunity.
Our strategy to support our clients with digitization opportunities focuses on an open platform approach.
This makes our desktop and content assets available to customers so they can leverage our capabilities, and those developed by our strategic partners, in order to develop their own workflow functions.
Furthermore, we also enable customers to connect fragmented data sets and generate useable meta-data out of textual information.
Our Labs™ data science team is on hand to support client-led sandbox ideation and Proof-of-Concept testing, as well as leading-edge AI tools from our technology partners to generate deal related insights.
This is not a mass produced approach for us.
We work with our clients to find the best way to implement these opportunities, based on their particular strategy, intellectual property and goals.
That is because no matter how disruptive the technology, its application and effectiveness will ultimately depend on the strategy of each firm. There is no single formula in which digitalization of investment banking can be deployed.
Instead, those financial institutions most likely to drive competitive advantage with a digitalization transformation agenda are those who explicitly determine where they want to focus their technology investments which will drive differentiation for them and will be difficult to replicate.
And we have the capabilities and flexibility to empower their agenda.
The growth of big data opens up opportunities for investment banks in terms of sources of information, while the development of artificial intelligence can turn this information into answers.
Find out more about how machine learning can be used to predict M&A opportunity by registering for our on-demand webinar.
The panelists are:
Sofia Spencer, Head of Digital — Investment Banking
Leon Saunders Calvert, Global Head of M&A and Capital Raising
Ryan Roser, Director — Data Science & Text Analytics