EY’s recent global corporate reporting survey tells us that change in corporate reporting is accelerating. In particular, the need to better communicate an organization’s ESG performance puts significant pressure on finance managers responsible for its preparation, forcing finance teams to strengthen their analytical capabilities.
Late last year, more than 1,000 CFOs, CFOs and senior CFOs from large enterprises in 26 countries, including 250 in Asia-Pacific, were surveyed to understand the challenges they face in corporate reporting.
The main theme that emerges from this research is that, alongside traditional financial reporting overseen by finance executives, investors and other stakeholders want consistent and credible ESG information on material issues to help them understand how a company is creating long-term value and sustainable growth.
EY survey participants aren’t the only ones noticing this trend. At EY, we see increasing pressure on companies to improve their ESG reporting – from equity investors, insurers, lenders, bondholders and asset managers, as well as clients. who all want more detail on ESG factors to assess the full impact of their economic decisions.
THE KEY TO ADVANCED ANALYTICS FOR ESG METRICS AND PERSPECTIVES EXTRACTION Extracting ESG insights from data is complex and time consuming – an almost impossible manual task. This requires the use of advanced analytics, which are now available to help companies structure, synthesize, interpret and derive insights from big data, and create credible and useful ESG reports. Advanced analytics is particularly important in ESG reporting due to the need to process and link large amounts of unstructured data.
Not surprisingly, the EY Global Corporate Reporting Survey found that the top technology investment priority for finance leaders over the next three years is advanced and predictive analytics. This priority is particularly felt in Asia Pacific where 47% of regional respondents (68% in China) versus 38% of global respondents have analytics as a technology investment priority.
DATA VOLUME AND QUALITY ARE ALWAYS PURCHASING BLOCKS
Yet even as finance teams seek to invest in analytics and build a more agile approach to financial planning and analysis, several data challenges stand in the way. According to participants in the EY Asia-Pacific survey, the main barriers are the sheer volume of external data, followed closely by issues of data quality and comparability. Lack of timely data and inefficient data integration are also problematic.
Analytics starts with data, but techniques such as predictive modeling, statistics, and visualization are also important in turning that data into timely and actionable insights.
For example, organizations can improve the quality of reports by introducing forward-looking information, using external data to corroborate and provide analysis of future trends. Subsequently, this downstream report output can be used to streamline upstream activities, such as capturing data in the correct format to enable efficient collection and analysis.
However, this requires proper planning, from data collection to reporting, with technology as a key enabler. In other words, this process should be considered part of an organization’s digital transformation journey.
ESSENTIAL COLLABORATION TO CREATE NEW ANALYTICAL CAPABILITIES
Deploying these types of advanced solutions requires more than finance teams buying new technology. It will take an interdisciplinary effort that combines advanced data science skills, business domain expertise, and finance and ESG experience.
Developing an approach that mimics human efforts is a guided process. It’s not just about developing algorithms, it may require learning and integrating human decision-making. The finance team will need to work with key stakeholders, such as analytical centers of excellence, to define use cases for advanced ESG analytics, and then collaborate during the development process.
RESOURCES AND SUPPORT NEEDED TO ACHIEVE EXCELLENCE IN REPORTING
Better non-financial corporate reporting, underpinned by advanced data analytics, will be essential to meet the changing needs of investors and stakeholders. Finance leaders need to drive innovation by building a bold technology roadmap to transform financial analytics and deliver improved and trusted reporting, including advanced tools like AI (artificial intelligence).
To support them, boards should assess whether finance leaders have adequate resources and budgets to address these challenges and increase their use of advanced data analytics to deliver stronger non-financial corporate reporting.
This article is provided for general information only and does not replace professional advice when the facts and circumstances warrant it. The views and opinions expressed above are those of the author and do not necessarily represent the views of SGV & Co.
Aris C. Malantic is a Market Group Head and Head of Financial Accounting Advisory Services (FAAS) at SGV & Co., as well as Head of EY Asean FAAS.