AP Automation: Key terms you need to know

The world of AP Automation is constantly evolving, and for those outside the tech sphere, the terminology can be confusing. To help, we've created an overview of essential terms and approaches in automated accounting and automated invoice processing.

Although software providers and accounting firms may sound similar when discussing AP automation, the underlying technology can differ significantly. There are also differences between what is available today and what will emerge in the future. Here are some of the most important technologies that modern finance and accounting departments should be familiar with:

Intelligent Automation (IA)

Intelligent Automation (IA) is a broad term that encompasses various "intelligent" solutions for automating processes such as accounting. For finance departments, this means optimizing workflows, reducing manual errors, and enhancing decision-making through advanced technologies like Artificial Intelligence (AI), Business Process Management (BPM), and Robotic Process Automation (RPA). IA often combines these technologies to achieve better results, such as integrating AI with RPA to manage more complex tasks in AP Automation.

Robotic Process Automation (RPA)

Robotic Process Automation (RPA) automates repetitive, rule-based tasks by mimicking human actions within existing systems. For finance departments, this translates to automating time-consuming tasks like data entry, invoice processing, and reconciliations. While RPA is a subset of Intelligent Automation, it doesn't involve artificial intelligence. RPA is ideal for simple, routine tasks, but it requires ongoing maintenance as the rules must be updated whenever conditions change. According to Gartner, RPA provides a quick, non-invasive integration solution but may not always be sufficient for implementing effective and flexible digital business processes.

Rule-Based Accounting

Rule-Based Accounting involves the manual upkeep of a set of rules. When a transaction is imported, it’s assigned an account number based on these rules. This can save time and ensure that similar transactions are consistently recorded. Rule-based accounting is often integrated into ERP systems and is useful for standardizing accounting processes. However, it requires continuous maintenance, especially when regulations or internal accounting practices change. To address these challenges, some companies combine rule-based accounting with AI and machine learning to automatically adjust the rules based on data analysis.

Artificial Intelligence (AI)

AI has transitioned from being a buzzword to an integral part of our daily operations. Increasingly, businesses recognize the value of AI, using it for various purposes in both professional and private contexts. Deloitte defines AI as the development of computer systems capable of performing tasks that normally require human intelligence, such as learning, reasoning, and problem-solving.

For finance departments, particularly in AP Automation, AI can significantly enhance automation processes. AI continuously learns and adapts to new data without the need for manual updates, allowing it to automatically categorize transactions based on prior learning and data analysis. This reduces errors and saves time. AI algorithms can analyze and interpret financial data, identify patterns and anomalies, and even predict future economic trends.

According to Forrester, AI has the potential to revolutionize work by increasing efficiency, reducing costs, and creating new revenue streams. In the context of AP Automation, this means faster processing times, fewer errors, and a more streamlined process. AI also provides a competitive advantage by improving the accuracy of accounting and freeing up time for finance departments to focus on more strategic tasks.

READ MORE: Should the finance department know anything about artificial intelligence?

SEMINE and Machine Learning

SEMINE is an AI solution built from the ground up with machine learning as its core component. By leveraging machine learning, SEMINE understands both the content and context of invoices, enabling the system to automatically suggest accounting entries and categorize costs. This enhances AP Automation by increasing the degree of automation and improving data quality. SEMINE identifies patterns and contexts in the transactions, providing automatic suggestions for accounting entries and cost categorization. This allows the finance department to focus on exceptions, with SEMINE improving its performance as it learns from these exceptions.

Machine learning is essential for us to offer our clients increased automation, better data, and deeper insights.

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Unlock Your Finance Team’s Full Potential

In a world where efficiency and accuracy are critical, AP Automation technologies like AI and machine learning provide a significant competitive edge. By understanding and implementing these technologies, companies can achieve a more streamlined accounting process, reduce costs, and improve decision-making. This frees up time for finance departments to focus on more exciting and value-creating tasks, unlocking the full potential of the team. SEMINE has been a pioneer in this field since 2016, with over 10,000 satisfied customers using our proven AI solution today.