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The CFO Imperative: How to build trust and talent for tomorrow’s reporting technologies

CFOs should build trust into artificial intelligence and emerging technologies and refresh their talent strategy for a smarter future.

In brief

  • Finance leaders should build trust into finance and reporting technology, including artificial intelligence (AI).
  • Finance leaders should map out potential new AI risks and the relevant governance frameworks and approaches.
  • Finance leaders should rethink their talent strategy for an AI-powered future.

Artificial intelligence (AI) offers an exciting opportunity for finance and reporting teams. In corporate reporting, AI can source information from a business’s public statements, and facilitate fraud analytics and analysis of balance sheets and performance. It can also play a central role in organizations building a better understanding of long-term value. To realize this potential, finance leaders should build trust into their systems and data outputs, understand and manage any new risks that emerge, and find the talent to exploit these smart systems.

AI has potential to play an important role in corporate reporting. The speed and efficiency of the technology is far beyond human capability and is available on demand. It also provides the potential for continuous improvement – through machine learning, AI learns and improves upon the tasks it has been asked to perform. And it can save time – AI carries out repetitive and monotonous tasks, freeing up resources to focus on activities that require judgment, creativity or experience. However, as the 2020 EY Global Financial Accounting Advisory Services (FAAS) corporate reporting survey highlights, realizing the potential of AI means actively confronting trust issues and finding the talent required to turn technology potential into reporting and finance reality.

Building trust into AI

Trust is the foundation on which organizations can build stakeholder confidence in AI systems and the insights they produce. However, building trust is difficult in an environment where governance, controls, ethical frameworks and regulations still struggle to keep up with the pace of change in cognitive computing. For example, more than two-thirds of respondents surveyed (68%) said, “governance, controls and ethical frameworks still need to be developed and refined for AI.”

Without those frameworks, finance leaders are concerned about the risk implications of AI: 63% of respondents said they “have concerns about the risks of using AI in finance and reporting, from security threats to regulatory risk.” That’s barely changed from the 64% of respondents who said the same in the 2019 survey. At the same time, many finance leaders do not have complete trust in the output of these systems: 47% of respondents said, “the quality of the finance data produced by AI cannot be trusted in the same way as data from our usual finance systems.” While this is an improvement on the 55% recorded in 2019, it still means close to half of all finance leaders remain unsure.

It is clear that a lack of trust in AI outputs is an issue for a number of respondents. However, these reservations could be more of a reflection of the lack of understanding of how these systems work. An alternative view is that AI and machine learning can potentially increase the credibility and accuracy of insights rather than detract from them. This rigor is due to the fact they arrive at conclusions based on a larger number of data sets, rather than an individual probing a single set of data and potentially introducing their own biases into the equation. It is therefore likely that smart machines could undertake data-driven tasks with greater accuracy, consistency and time-efficiency than humans.

So the question becomes: how can finance functions build trust into the AI they use to drive insight? Without it, stakeholder confidence in the AI is likely to prove elusive. The starting point is for finance leaders to understand and map some of the new risks that AI brings and to use these insights to begin to create the right governance and control mechanisms. To build trust in the outputs, AI should be trained properly, with appropriate boundaries around it at first. Then, after it is put into production to identify and rectify any flaws, its performance should be continually monitored. It’s another new demand of finance leaders, whose evolving responsibilities are examined in this CFO Imperative series, which identifies critical answers and actions to help leaders reframe the future of their organizations.

Rethinking the future finance talent strategy

The impact of AI could also be profound for the people in the finance team and how CFOs think about the future talent strategy. In the survey, 64% of respondents said a wide range of core finance roles – such as financial reporting, accounting and financial control – could be significantly disrupted and changed as a result of advances in automation and AI. The function’s skills profile is also likely to change dramatically in the future to be more digitally focused. As shown below, cognitive computing skills could be the most in-demand, followed by technology delivery and digital transformation. And as shown below, respondents said that cognitive computing is the most important skill required both over the next 12 months and the next 3 years.

Exploiting the potential of AI also requires certain data analytics skills to examine and develop insights. The survey found respondents put significant emphasis on “analytical and data science skills” over the next 12 months, with 20% identifying it as one of the most in-demand skills. However, when respondents were asked about their outlook for the following three years, this dropped to 11%. This could indicate that finance leaders are confident their ongoing skills-building initiatives – from hiring data talent to building the data analytics skills of existing staff – will have made progress.

However, leaders could still face challenges in providing confidence that finance has the skills required for the future. One particularly difficult challenge could be finding talent possessing skills at the intersection of digital and finance. The top three challenges are:

  1. Competing for finance talent combining reporting and finance skills with technology acumen, including data science and cognitive computing
  2. Making sure skills and capabilities keep up with the accelerated pace of technology change
  3. Building an effective learning culture so people are able to constantly refresh and reinvigorate their skills

As the survey has shown, leaders are very clear on the challenges that stand in the way of securing the skills they are likely to require to provide a new future for reporting, from competing for prized talent to helping people embrace continuous learning. Designing a future talent strategy for the function could be important to earning the long-term loyalty and commitment of creative and talented finance professionals, while meeting the challenges of constant change and disruption ahead. Embedding the continuous learning mindset could require a change in culture for the function. The 2020 EY DNA of the CFO survey found that 71% of respondents said, “traditional mindsets” are slowing the modernization of the function, and 73% of respondents said “changing the culture” of the finance team is a major priority.

And, of course, finance leaders cannot forget changes to their own roles. Helene Siberg Wendin – EY Global FAAS Deputy Leader – believes that while there are, of course, companies in which CFOs largely pursue “traditional” responsibilities, that change is inevitable in the future as finance leaders drive a wider C-suite agenda. “Finance leaders have a broader network today,” she says. “They are paired with the CEO, almost like two horses running side by side. They are connected to HR and talent questions: what kind of people should the organization hire in the future, how do we balance onshore and offshore, and what impact could digitalization have on jobs? With more organizations having a chief digital officer, the CFO should understand the impact of industry disruption and how the organization could connect with consumers in the future. If you want to be seen as a CFO who is a front-runner, you should have a broader view and strong connections with other key stakeholders in the C-suite.”

Summary

AI offers a significant opportunity to transform reporting, but AI applications come with risks that companies should seek to mitigate, and as a result, CFOs should rethink their talent strategy.

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