An article produced by Corporate Financier, ICAEW, June 2020  

The original article can be found here (page 12-13)

Featuring: APPG AI evidence findings on Corporate Decision Marking: Best Practice Guidelines for AI Adoption, published in this report. The video of the evidence meeting can be found here, and the photo gallery can be found here. Big Innovation Centre is the organiser and appointed Secretariat by UK Parliament for the group. 

Artificial intelligence (AI) is increasingly being used in corporate decision-making, investment and M&A. Last year, the faculty’s Shaun Beaney and Rosanna Woods of Drooms co-authored the AI in Corporate Advisory research report. This was
followed in May by an evidence meeting held by the All-Party Parliamentary Group on Artificial Intelligence (APPG-AI), hosted remotely due to the COVID-19 pandemic.

Chaired by Lord Clement-Jones CBE (who is also a member of the Corporate Finance Faculty’s board) and Conservative Party MP Stephen Metcalfe, the panel comprised representatives of the seven organisations that presented evidence for the APPG-AI report:

  • Jan Chan, TAS chief innovation officer UK, EY;
  • Dr Christine Chow, head of Asia and global emerging markets,
    Hermes Investment Management;
  • Naomi Climer CBE, co-chair, Institute for the Future of Work;
  • Sanu de Lima, deputy director, corporate governance reform,
    Department for Business, Energy & Industrial Strategy;
  • David Petrie, head of corporate finance, ICAEW;
  • Charles Radclyffe, former head of AI, Fidelity International; and
  • Dr Zoë Webster, director – AI and data economy, Innovate UK.

It was agreed that successful deployment of AI in corporate decisionmaking and investment required an efficient and coherent AI strategy across all phases, as well as regular audits of the deployed AI technologies. Furthermore, employees must be sufficiently trained.

Lastly, the government must work with businesses to safeguard the responsible use of AI, ensure the upskilling of the workforce and facilitate the supply of talent.

This article is a summary of the main points that the panel discussed and that were raised during the Q&A, which saw 300 experts join online. The detailed Parliamentary Briefing is at tinyurl.com/CF-APPG-AI

Dr Christine Chow,
Hermes Investment Management

When it comes to corporate decisionmaking and investing, AI can benefit businesses in three key ways.
Identifying opportunities: keyword searches and news screens identify strategic fit and funding needs that help potential acquirers build a pipeline of targets.
Regulatory technology enables near real-time legal and tax compliance checks. AI supports document management and processing for transactions. Big data-led factor analysis can be used to assess intangible qualities such as corporate culture and customer trust. Near-real-time location and asset-level data, such as satellite images and on-site sensors, help analysts to collect and process data directly rather than relying on disclosure-based methods.
Strengthening scenario analysis: interactive data visualisation helps decision-makers get past the noise of big data and makes analytics agile.
These upsides can be captured with success if the risks are managed.
Quantifying trust and culture requires a conscious choice of proxy indicators to measure them. The indicators may not
fully capture what needs to be assessed and could be situational, so decisionmakers should understand the rationale
and limits of them.
AI analytics are often associated with a degree of confidence in the results.
How do statistics and probabilities affect corporate decisions and pricing? Statistics refresher courses can help decisionmakers more confidently challenge the recommendations presented to them.
Companies should map out their group AI footprint and an inventory of algorithmic models, with board oversight for AI governance. This ensures group-wide consistency and efficient use of resources. They should publish AI principles that reflect business strategy, demonstrating transparency and accountability.

David Petrie,
head of corporate finance, ICAEW

The potential for the use of AI-based technologies in corporate decisionmaking is unquestionable, although applications are still at an early stage.
Machine reading and learning are already being deployed in virtual data rooms that are used throughout the M&A deal process – particularly on the legal side, for contract analysis and in financial analysis, modelling and scenario planning.
The greatest potential for the more widespread application of AI in the deal process is in, variously, origination, company valuation, due diligence and all-important post-transaction integration.
ICAEW supports responsible innovation by companies, financiers, and corporate advisers. This is vital for ensuring public trust.
We recommend that corporate finance practitioners adopt a principles-based approach that takes into account the ethical codes and protocols that have already been developed for professional services and for broader investment activity.
Therefore, we do not believe that specific new regulation of AI in corporate finance is necessary.
ICAEW suggests that guidelines for the use and application of AI in corporate decision-making and oversight by companies should: recommend appropriate and practicable levels of disclosure; include within corporate reporting requirements an explanation about how AI-based technologies have been deployed; ensure clarity about the various responsibilities of corporate executive and non-executive directors; and encourage measures that boost investment and innovation in AI,
rather than hinder them.

Jan Chan, EY

“AI is sometimes feared as a risk to jobs, but in the current situation we have the opportunity to utilise AI-augmented
decision-making to respond quickly to urgent challenges, which will be required in order to boost the post-COVID-19 UK
economy. AI will enable us to find solutions backed up with evidence-based computational statistics.”

Naomi Climer CBE, Institute for the Future of Work

“It’s important to be really clear about what outcome the AI is meant to achieve.
This then makes it possible to check that it’s doing what was intended. It’s essential to audit the AI to check for equality,
fairness, accountability, sustainability, transparency and data protection. It’s also necessary to take actions based on
the audit findings to mitigate any issues that emerge.”

Sanu de Lima, Department for Business, Energy & Industrial Strategy

“One practical application of AI is around high-volume information analysis.
For corporates in the first instance the application of AI could be really beneficial, partly given the increased demands on public companies when it comes to corporate reporting, and the number of things they have to report on. In light of the COVID-19 situation, we are looking at increased flexibility for equity raising in the market. It’s increasingly important for market supervision to be able to monitor quick developments – for example for flexibilities for pre-emption rights in terms of raising equity.”

Charles Radclyffe, formerly Fidelity International

“What’s true of firms who have made the most of AI-based technologies is that they’ve done three things: recognised long-term competitive advantage that a data-centric approach can bring; built the capability to deliver on this; and largely put in place the governance mechanisms to ensure the engine doesn’t fall off mid-flight. Boards and investors should take note of these themes and work to understand how to implement them in their own operations or investments.”

Dr Zoë Webster, Innovate UK

“The impact of AI will not be limited to a single sector or solely to the firms that develop and produce AI tools and technologies. Many sectors have started to identify and pursue specific opportunities to use AI. This may be to boost
productivity in their specialised processes or to increase competitiveness and sales through the development of new or improved products, processes or services for the market, such as to develop more personalised financial products.”

The meeting was co-ordinated by Professor Birgitte Andersen, chief executive of the Big Innovation Centre and Dr Désirée Remmert, the centre’s AI lead.

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