How to create trusted reporting on corporate culture

A recent EY survey looked at how data analytics and artificial intelligence can help close the culture reporting disconnect.

Today, corporate reporting is coming under significant pressure to meet stakeholder demands for greater openness and transparency. In particular, nonfinancial reporting is critical to its continued relevance: 74% of finance leaders who took part in the sixth EY global corporate reporting survey, Does corporate reporting need a culture shock?, say that investors increasingly use nonfinancial information in their decision-making, and 72% say that focusing purely on financial reporting offers only a partial view of the company’s value-creation framework. Stakeholders increasingly want to see how companies are creating long-term value.

One of the most important nonfinancial metrics is corporate culture. The survey shows that finance leaders don’t see this as a “soft” issue that has little to do with the value of their organizations. On the contrary, they view it as central to growing and protecting enterprise value: 83% agree that “a healthy corporate culture where values or behaviors are consistently lived is critical to building trust,” while 81% agree that such a culture can help reduce risk. They are also clear about the risks presented by a harmful corporate culture, with 77% agreeing that it is one of the most significant threats to sustainable value.

However, while 79% of finance leaders say investors increasingly want more insight into company culture, and the same percentage say they have the data volumes today to give stakeholders the cultural insight they want, only 37% say their organization actually provides ongoing performance reporting or key performance indicators on this area.

So, what is holding them back? The major concerns are over controls and data quality – see graphic, below.

To bridge this culture reporting disconnect, companies therefore need to identify the behaviors, values and beliefs that make up their culture; decide which elements of that culture to measure; and devise quantifiable metrics to assess and report on performance.

The role of data analytics

The finance team has a critical role to play here, particularly in agreeing on the metrics for assessing corporate culture and demonstrating how they correlate to financial performance. However, this will create additional work for finance teams with limited resources, and it will require individuals who are more used to working with technical accounting standards to focus on nonfinancial areas.

In other words, developing and reporting on nonfinancial metrics may require a change in the culture within the finance team itself. Only 35% of those surveyed say their finance teams play an end-to-end role in nonfinancial reporting, with significant involvement in collecting, analyzing and assuring it.

One practical way in which companies can help to push through this culture change is by deploying advanced data gathering and analysis technologies. In particular, robotic process automation (RPA) allows time-consuming tasks such as data gathering to be completed more efficiently, while artificial intelligence (AI) gives a new depth of insight to reporting.

But the survey results suggest that these technologies are only slowly gaining traction in the finance function. Only 30% of the financial controllers surveyed say they have a scaled solution for automating data collection for corporate reporting, and fewer than that have deployed AI for tasks where it might typically prove valuable.

A further issue is the need to assess the data outputs from these technologies to ensure they are credible and trusted. For example, 60% of group CFOs surveyed say the quality of the data produced by AI cannot be trusted in the same way as data from their usual finance systems; 66% say the global regulatory environment has not yet caught up with developments in AI; and 75% say that governance, controls and ethical frameworks for AI still need to be developed and refined.

To address these concerns, and to build trust into AI systems, the report suggests four questions for finance leaders to ask themselves:

1.  Do you know where AI technologies are being applied within the organization, particularly in terms of nonfinancial data or information that makes its way into corporate reporting?

2.  Do you have a talent strategy for recruiting and retaining people with the necessary skillsets to manage and staff AI-related projects, including issues of trust and ethics?

3.  Have you assessed how the adoption of AI impacts the integrity of the finance function and its disclosures, both financial and nonfinancial?

4.  Does the finance team have appropriate structures in place to manage ethical issues and understand how to address any algorithmic biases?

Culture reporting: the way forward

The report recommends three actions organizations should take to drive the critical role of culture in corporate reporting:

1. Put in place a robust approach to culture reporting

Four steps are critical. First, understand the overall scope by looking at a range of culture-related risks and mapping the beliefs of your people. Second, identify the behaviors, values and beliefs your people are observing to establish current and desired cultural attributes, and assess cultural norms and nuances. Third, assess how those behaviors, values and beliefs affect your organization’s performance. Finally, identify metrics and dashboards, using the results and insights to inform leadership action and form the basis of reporting.

2. Change the talent mix to drive finance culture change and overcome resistance

The culture of finance functions is likely to have become ingrained over many years. To overcome resistance to change, and drive sustainable culture change, finance leaders should inject new ideas and fresh impetus into the team. Changing the finance and reporting talent mix may provide an important lever for culture change.

3. Build ethical algorithms and trust into AI

If organizations fail to adopt governance and ethical standards that foster trust in AI, they may not be able to harness the full potential of these technologies in finance and reporting. Organizations should commit to building trust proactively into every facet of the AI system from day one. This trust should extend to the strategic purpose of the system, the integrity of data collection and management, the governance of model training, and the rigor of techniques used to monitor system and algorithmic performance.

Peter Wollmert, EY Global and EY EMEIA Financial Accounting Advisory Leader, concludes: “By embracing the role of culture in corporate reporting, finance leaders can provide the transparency that investors and other stakeholders require, building a new era of trust based on credible, authentic, accountable and open corporate reporting.”