Leveraging Artificial Intelligence to Optimize the Monthly Close Process
Artificial intelligence and machine learning are rapidly transforming the accounting industry, and financial leaders need to adopt these technologies quickly to stay competitive. Tony Klimas, President of Horváth US, points out that by integrating AI and ML tools, companies can automate over 70% of a typical close process, shorten close time to the third day of each month, and allow finance teams to focus on high-value activities. The article explores pathways to technology-driven close modernization, common obstacles, and best practices.
Editor's note:Tony Klimas is a partner and president of Horváth US, a global management consulting firm headquartered in Atlanta, Georgia. The views expressed in this article are solely those of the author.
Artificial intelligence (AI) and machine learning (ML) are profoundly reshaping the accounting industry, and financial leaders must act quickly to leverage cutting-edge digital tools, or risk putting their organizations at a competitive disadvantage. An ideal starting point is integrating these technologies intothe acceleration and optimization of the monthly close process, thereby allowing accounting teams to devote more time to other value-added projects.
Efficiency optimization is a key goal for organizations of all types to boost productivity, reduce costs, and gain a competitive edge in their industries. Most business executives, including chief financial officers (CFOs), are well aware that core processes hold significant optimization potential. However, the challenge for executives lies in charting a realistic and executable path to improve these core processes and achieve best-in-class execution.
Cost competition pressures continue to drive companies to enhance employee productivity and operational efficiency, and the potential of new technologies such as robotic process automation (RPA), process mining, machine learning, and artificial intelligence further intensifies this pressure. Savvy accounting leaders have seen the trend and are actively seeking to integrate these technologies into their teams' daily tasks, including the monthly close. A recent Gartner survey confirms this:45% of executives said the widespread attention on ChatGPT "prompted them to increase their AI investments"。
Horváth's experience working with clients shows that over 70% of tasks in a typical close process can be automated. This not only frees up finance staff time to focus on value-added activities such as decision support and business commentary, but also allows for a reduction in the size of the team responsible for the close.
One of the key drivers of efficiency optimization in the accounting domain is the adoption of "tier-one" digital technologies, such as business intelligence (BI) tools that integrate AI and ML code. BI technology enables companies to quickly and accurately access, aggregate, analyze, and visualize accounting data, while providing business leaders with critical insights to support decision-making and drive process improvements. Furthermore, BI technology helps companies identify areas within the accounting function that can be further optimized and track the effectiveness of improvement measures over the long term.
Such technologies help connect disparate IT systems and applications, enabling companies to break down information silos within the accounting department (e.g., accounts payable, accounts receivable, inventory management, payroll, etc.). Improved data sharing and collaboration lead to more streamlined processes and faster decision-making, meaning efficiency gains can span multiple subsidiaries, business units, and the accounting function itself.
Modernizing the Close Process
For years, companies have strived to achieve a close process that provides access to data on demand (i.e., a "continuous" or "modern" accounting model). Achieving the goal of a "soft close" (which can be completed on demand) is highly dependent on a streamlined close process that completes the financial close in the shortest possible time.
This approach requires moving some tasks into daily accounting work, such as intercompany reconciliations, currency translation, accrual postings, and goods receipt/invoice receipt transactions. Adopting this approach can shorten close times, with the entire process completed by the third day of each month.
Common practices that lead to extended close cycles include: inconsistent manual execution of the close calendar; decentralized document storage and archiving; limited governance due to a lack of transparency and real-time information; and limited automation application (e.g., relying only on batch jobs or basic robotic capabilities).
Achieving Technology-Driven Results
Standardizing, simplifying, and automating tasks and processes enables organizations to achieve more consistent service quality, streamlined operations, and increased accounting team productivity. By reducing complexity and eliminating redundancy, companies can save time and resources in the close process, thereby improving profit performance.
Implementing advanced cloud-based close management software should include the following key features: replacing outdated tools like Excel and RPA with a single cloud SaaS solution; low maintenance costs through a "low-code/no-code" interface; support for automated account reconciliations and periodic financial health checks; and providing an accelerated and transparent audit trail.
Over the past decades, change in the close process has been more evolutionary than revolutionary. Today, BI tools incorporating AI and ML are reshaping the monthly close, making it simpler, highly automated, and efficient.
The monthly close should not be a burdensome task. Companies that leverage the latest technologies can turn it into a value-added activity while freeing up time for strategic initiatives.