Technology is transforming finance, particularly in the area of data. Today, organizations and their finance teams have more data than ever before, thanks to increases in computer processing power, ever-growing connectivity, and the cloud and its massive storage capacity.
However, many finance and reporting teams are overwhelmed by the volume and variety of that data. Almost half of the finance leaders (49%) interviewed for the 2018 EY corporate reporting survey, How can the digital transformation of reporting build the bridge between trust and long-term value?, say they “spend more time gathering and processing data than they do in analyzing it”.
The time finance teams spend on gathering and validating financial data means that they have been focused on producing compliant financial information rather than making progress on nonfinancial reporting. To turn data into truly value-driven reporting, finance teams should focus on utilizing technological advances in areas such as automation, artificial intelligence (AI) and blockchain, and on building trust in data analytics. This digital transformation also requires them to think differently about the people they recruit.
Automation: giving finance teams freedom to focus on insight generation
The most agile finance and reporting teams are advanced in using robotic process automation (RPA) to drive new levels of efficiency and are using rules-based robotics technologies to automate high-volume transactional finance processes.
They are also exploring the next frontier in automation – intelligent process automation, which combines RPA with AI such as machine learning. These technologies learn over time as they are exposed to more data. Lease accounting changes are one example; pilots have shown that AI tools can review about 70% to 80% of the content of simple lease contracts. As these tools improve, they will move on to reading, managing and analyzing complex contracts and data.
Automation is crucial for giving busy finance teams the space to develop the reporting insights that create transparency and trust. Automating key elements of delivery – both transactional tasks and more complex ones – can free them up to focus on data-driven reporting insight, turning data into a strategic asset.
AI: harnessing insight from data
Finance leaders can use AI to look for underlying patterns in data, and machine learning to predict scenarios and improve outcomes. Almost three-quarters of finance leaders in the EY research (72%) say that AI will have a significant impact on the way finance drives data-driven insight, and that it will be the critical technology for the finance function in the future.