Emerging trends in Financial Consolidation: Non-Financial Data, AI and ESG Metrics
Consolidation is sometimes viewed as the ‘engine room’ of finance. It plays a crucial role in providing accurate and reliable financial information for organizations across many industries. However, as businesses face mounting business complexity, regulation and compliance, the design of legacy consolidation systems (especially those that are on-premises) is starting to unravel. This is because data management is becoming the pre-eminent concern and legacy consolidation systems designed around the capture of monthly balances are ill-equipped to deal with the complex data demands of the modern era.
Modern financial consolidation systems have to accommodate much more granular, voluminous and varied data, whether that be financial and operational data for performance reporting, multi-year comparative history for generating AI insights or specialized ESG (Environmental, Social and Governance) data and metrics.
Yet, despite these profound changes, few organizations have invested in future-proofing the financial consolidation process. FSN’s 2021 research1 entitled, "Agility in Financial Reporting & Close", showed that only 11% of companies had completely transformed their financial close process.
So what are the key challenges for the foreseeable future, and how can modern finance functions future-proof the financial close process?
The Evolving Landscape of Data Integration
One of the pronounced trends in recent times has been the increasing need to merge highly granular financial and operational data to drive business insight and decision-making. In turn, this has compelled organizations to look more broadly at unstructured financial and non-financial data sources, that are frequently more granular and varied. This shift away from strictly codified and familiar financial data puts strain on the financial close process in three key areas.
Firstly, the need for consolidation software to provide data accessibility and collection tools that enable the finance function to quickly ingest a variety of data sources without heavy IT involvement. Secondly, the ability to automate data capture and validation controls to maintain a high level of data quality over these new data sources. Thirdly, the need for malleable and extensible consolidation models, that can readily accommodate more diverse and asynchronous dimensions that reflect the new reality of more complex and challenging data.
Opportunities for AI in Finance
Artificial intelligence (AI) and Generative AI – Chat GPT-like experience - has stormed to the top of the CFO agenda, even if it's only temporarily. But it opens up a broader discussion about how companies prepare for an era of AI in finance. It's still early days, but software vendors like Wolters Kluwer with its CCH Tagetik expert solution, are keen to build AI capabilities into their platform solutions.
Strong use-cases for AI include the automation of data capture that could accelerate the consolidation process. AI could be used to ensure consistency in the data gathering phase by accelerating the tedious process of mapping tables between source data and the consolidation system. It can be used to accelerate data validation by investigating data anomalies and outliers. It can be used to accelerate analysis by identifying the hidden drivers who impacted or contributed the most to your performance, so to enrich with consciousness the story of your results.
On the other hand, Generative AI, could be used to automatically generate, narrative and disclosures which could save a lot of time in the final stages of financial reporting. However, AI needs good data in order to provide rich insights, and FSN’s research2 finds that only 53% of businesses have at least 5 years of historic data to work with.
Lastly, natural language processing (NLP), which allows for speech-based report generation, is clearly within reach. Also in this case CCH Tagetik expert solution from Wolters Kluwer is seeking to develop embedded proprietary AI capabilities which are relevant and easy to use.
Challenges and Opportunities for CFOs in the ESG Era
In the new era of ESG, CFOs will be thrust into an environment of unfamiliar environmental and other data, which is more forward looking, unaudited and frequently estimated. The breadth of ESG directives will add to the challenges. From diversity policy and recruitment, through to sustainability and social initiatives, ESG will be characterized by a cross-functional, multidisciplinary effort involving a large number of different stakeholders. Coalescing these different perspectives and providing unified reporting will require advanced consolidation capabilities in which all stakeholders can collaborate in a unified and consistent reporting environment.
The Role of Data Management and Extensible Consolidation Models
Weaving its way through all of the near-term challenges of financial consolidation and reporting is data management. Whether it's having the modern tools needed for the speedy acquisition of data, furnishing enough data to satisfy artificial intelligence or being able to accommodate the varied data requirements of ESG, astute finance leaders are aware that they will need to rely on extensible and scalable consolidation models – if not now, in the very near future.
To hear more about this topic watch our on-demand webinar “How Can CFOs Make Financial Consolidation Fit For The Future?”
Note1 FSN’s 2021 research entitled, "Agility in Financial Reporting & Close."
Note2 FSN Global Survey 2020/21 "The Future of Analytics In The Finance Function."