Automating Journal Entries: How AI is Eliminating Month-End Stress for Finance Teams

The month-end close continues to be a primary contributor to stress in finance teams. The number of tasks requires long hours accompanied with increased levels of burnout. A survey by FloQast indicates that over 60% of all finance professionals stated they feel stressed more during the month-end close. Even more alarming, 25% said this stress drives employee turnover.However, artificial intelligence (AI) is changing this fundamental process. AI is allowing for journal postings to be automated and simplifying the entire financial close process. AI software can scan much larger amounts of data than a human can well ahead of the month-end close and can reduce the month-end close time frame from weeks to hours. On average, companies automating their financial close process with AI are closing their books 32% faster than companies continuing to apply manual accounting methods. Automating the process is not just faster, it is minimizing errors, and organizations in total are benefiting from enhanced performance, including enabling the finance teams to spend more time on strategic decisions and analysis.

The Traditional Challenges of Month-End Close

When it is time for month-end closings, finance teams generally endure a cumbersome cycle. Usually, this is subject to manual work such as payment reconciliation, verification, or data entry. These tasks are not only time-consuming, but they can also be prone to human error, which can result in less than accurate financial statements. Medius found that 55% of finance professionals experience burnout from doing the same tasks over and over again, and 58% even considered leaving the finance profession altogether. These traditional processes concern themselves with spreadsheets and disjointed systems that generally run late in reporting, ultimately delaying timely decisions across the organization. A study by SAP Insights states that if the month-end process is ineffective, the closing could increase by as much as 50%, which could have a material impact on organizational adaptability.

How AI Automates Journal Entries

AI-powered tools can link systems to automate journal entries, import information and apply rules that have been established. This includes machine learning rules and Optical Character Recognition (OCR) for extracting and categorizing the transaction data and costs from invoices, receipts, and bank statements. Below is an example:

• Data Entry Automation

Automated data entry utilizing AI capabilities can reduce finance team workload by as much as 80% simply by requiring less human engagement. This drastic reduction in manual input has the potential to save valuable time and decrease the chances of errors significantly. Manual data entry is subject to human error, which can yield inaccurate financial documents that need to be fixed. Automating this process with an AI application guarantees accurate scrutinizing of information capturing and processing. It enables finance personnel to take that time and deploy it to higher value work like financial analyses and planning strategically. For example, AI may use Optical Character Recognition (OCR) technology to extract usable information automatically from invoices, receipts, and bank statements and then categorize the information and input it into the financial system. All records will have timeliness, consistency and accuracy mapped onto the financial system as usable data points.

• Automated Reconciliation

AI technology is transforming the payment reconciliation process as it provides the ability to match transactions across different systems in a matter of seconds. The speed and efficiency of AI technology means reconciliation, and other discrepancies, can be flagged that would otherwise take days to review, or may even go unnoticed altogether. Items flagged by AI are then ready for a human review, which takes significantly less time to address. The importance of automated reconciliation is amplified for organizations with complex financial structures that have multiple accounts and systems. AI enables finance teams to scan through large quantities of data to ensure all transactions are captured and reported in order to mitigate the risk of material misstatement. KPMG reported that using automated reconciliation can reduce the time it takes to conduct reconciliation by more than 50%This speeds up the completion of month-end closes, allowing finance teams time to focus on other critical areas of financial management.

This automation allows accounting staff to shift their focus from manual tasks to higher-value activities, such as analysis and strategy.

Efficiency Gains Through Automation

AI significantly accelerates the financial close process. According to research by SAP Insights, AI tools can analyze large volumes of data faster than humans, reducing the time required for month-end closings from weeks to hours.

Key benefits include:

• Faster Accounting Closes
  

Companies harnessing AI in their financial close processes have quicker close results. On average, AI users close their books 32% faster than users of manual processes. In addition, faster closes mean quicker access to financial information and more timely and effective strategic and operational decisions. In SAP Insights, it stated that AI-driven automation reduces closing time as it can complete tasks like entering journal entries and completing reconciliations instead of humans. AI can decrease overall closing time and increase overall efficiency.

• Continuous Close
  

AI also can deliver a continuous close by aiding with daily bookkeeping tasks. In many cases, it pulls the monthly paperwork together over the month, relieving the concentration of work at the end of the month. A regular job is less stressful than work for a month all at once. AI allows finance teams to automate routine tasks while they can spend their time on higher value tasks all month, rendering a smoother and efficient financial closing process. AI and continuous closing will assist in keeping financial records up to date, and will enhance visibility while decreasing errors.

These improvements not only reduce stress but also provide earlier access to critical financial information for decision-making.

Improved Accuracy and Fraud Detection

Manual journal entries are often prone to errors, which can compromise the accuracy of financial statements. AI tools have emerged as a powerful solution to enhance both accuracy and reliability in this area. These tools are highly effective at identifying anomalies within large datasets—far beyond what humans can detect. According to Deloitte, machines are especially skilled at spotting errors in spreadsheets containing thousands of cells.

The advantages go beyond just accuracy. Automated processes minimize manual intervention and strengthen internal controls, which can lead to a reduction in fraud risks by up to 40%. Additionally, AI systems facilitate the digital storage of supporting documents, simplifying the audit process. This not only reduces effort but also helps lower audit-related fees for all parties involved. Altogether, these features ensure compliance and build greater trust in financial reporting, marking a major advancement in modern financial management.

Cost Savings and Resource Optimization

By automating journal entries, organizations can realize considerable efficiencies in time and money. Automation replaces tedious tasks such as manual data entry and reconciliation with automation, which frees up 54% of time for further innovation strategies .This transition allows finance teams to carry out higher value activities like forecasting rather than repeating tasks. Furthermore, a digital approval process eliminates bottlenecks and enhances collaboration across departments, which replaces manual approvals. These benefits not only decrease operational costs associated with paper retention and manual tasks, but also create a much more productive and agile finance function.

AI enables a “continuous close” by simplifying daily bookkeeping activities. This spreads the workload across the month rather than front loading activities at month-end, reducing the pressure and stress that exists with month-end close. AI allows the finance team to focus on higher value activities during the month by automating repetitive tasks. This ultimately leads to a better monthly close. An additional benefit of keeping up with issuing records also enhances visibility and reduces errors.

The Human Element: Redefining Roles in Finance

Although AI is proficient in automating repetitive tasks in finance, the human element is still critical in solving complex issues and making more ethical decisions. SAP Insights reveals that critical thinking and communication skills are among the capacities least influenced by automation. AI serves as a complementary tool to support human intelligence with additional insights and data-driven recommendations.This partnership can be a major strength for professionals in finance, enabling them to dedicate their time toward relationship-building and strategic decision-making. Finance professionals now have access to AI-generated insights and can use those new insights while making decisions around innovation and complex financial issues that require expert judgment and contextual knowledge.

Adoption Trends: A Growing Demand for Automation

The push for AI automation in finance is gaining significant momentum. A recent survey by NVIDIA reveals that 91% of financial services companies are either assessing AI or already using it in production. This widespread adoption reflects the industry's recognition of AI's potential to enhance operational efficiency and drive innovation. Contrary to job displacement fears, professionals view AI as a tool to augment their roles, enabling them to focus on higher-value tasks. This positive outlook is driving continued investment, with 97% of companies planning to increase their AI spending in the near future.

Conclusion: Transforming Finance Teams with AI

AI is revolutionizing journal entries and the broader month-end close process by automating repetitive tasks, improving accuracy, reducing fraud risks, and enabling faster closes. These advancements not only alleviate stress but also empower finance teams to focus on higher-value activities. With adoption rates climbing and proven benefits such as 32% faster closes and up to 40% fraud reduction, it's clear that AI is no longer a luxury but a necessity for modern finance teams. As organizations continue investing in AI-driven solutions, they pave the way for a more efficient, accurate, and innovative future in financial management.