AI Accounting Glossary

In accounting and finance, accuracy refers to the exactness and precision of data and transactions. Ensuring accuracy minimizes errors and enhances the reliability of financial statements and reports. AP software can help increase data accuracy.

AP represents the money a company owes to suppliers or vendors for goods or services received. It is a critical component of a company's short-term liabilities on the balance sheet.

In finance, accountable AI refers to implementing artificial intelligence (AI) systems that are transparent, ethical, and compliant with regulatory standards. It ensures that AI-driven decisions are explainable, fair, and responsible, enhancing trust and reliability in financial operations. During an AI integration, ensuring the vendor is reputable and meets industry standards for data handling and storage is critical.

The process of using technology to automate the AP process, from invoice receipt to payment. AP automation reduces manual work, increases efficiency, and minimizes errors.

Technology consisting of machine-learning algorithms and data models designed to perform day-to-day tasks that typically require human intelligence, including data extraction, processing, and analysis.

An AI algorithm in finance is a set of rules and calculations used by AI systems to analyze data, identify patterns, and make decisions, thereby improving efficiency and accuracy in financial operations.

A virtual assistant powered by AI that performs common accounting tasks such as invoice processing, data entry, account reconciliation, and financial analysis. It helps finance professionals automate routine work, increasing efficiency and accuracy.

 AI accounting software leverages AI to enhance traditional accounting and automation processes, and offers capabilities beyond a traditional AP software solution. It hyper-automates routine tasks like invoice processing, expense management, and financial reporting, providing real-time insights and reducing manual effort.

An AI assistant is a virtual team member typically leveraging conversational AI that can perform simple tasks such as answering queries, handling repetitive work, generating reports, and providing financial insights. It can also enhance productivity by handling routine tasks, allowing finance professionals to focus on strategic activities.

This term refers to anomalies or patterns identified by AI systems, such as invoice discrepancies or potential fraud, allowing finance professionals to take proactive measures.

 AI integration involves incorporating AI technologies into existing financial systems and workflows. An AI integration can add advanced capabilities such as data analysis, decision-making, and process automation, improving efficiency, accuracy, and operational performance.

The systematic review and analysis of data to uncover specific patterns, correlations, and insights that can inform decision-making and actionable strategy.

 Involves data analysis tools to gain insights into specific AP software, processes, or functions. These insights can help finance teams optimize workflows, reduce costs, and improve decision-making by analyzing trends and performance metrics.

This is the sequence of steps an invoice goes through for review and authorization before payment. Approval flows are an ideal candidate for AP automation to streamline the process, reducing bottlenecks and ensuring compliance.

 AP autonomy refers to using AI to fully automate the AP process, from invoice receipt to payment. This eliminates the need for human intervention, increasing efficiency, reducing errors, and speeding up processing times.

A chronological record of all transactions and activities related to financial data. It ensures transparency and accountability, making it easier to track changes and verify records' accuracy during audits.

Autonomous accounting is the practice of using AI to automate end-to-end accounting processes without human intervention. Autonomous accounting is a modern approach to traditional AP software, which typically has only automated a particular task or activity within a process. Autonomous accounting involves an AI integration to handle tasks like invoice processing, approvals, reconciliation, and financial reporting, allowing teams to reallocate time and focus on more strategic activities.

Autonomous invoice processing uses AI to handle the entire invoice workflow, from data extraction to approval, without human involvement. This increases efficiency, accuracy, and speed, freeing up finance teams for more strategic tasks.

Autonomous purchase order (PO) matching leverages AI to verify that invoice details align with corresponding purchase orders and receipts. This improves accuracy, speeds up invoice processing, eliminates errors, and reduces manual effort.

A “hands-free” feature in the Vic.ai platform that automatically handles repetitive invoice processing and bill pay tasks without human intervention, enabling finance teams to focus on more strategic activities.

The agreed-upon conditions under which one business will pay another for goods or services. AI can detect and flag these terms to help leaders improve cash flow and strengthen supplier relationships.

Financial transactions between businesses for goods or services. AI can streamline and secure these payments, enhancing efficiency, reducing processing times, and minimizing the risk of fraud.

Compliance automation uses technology to ensure that financial processes adhere to regulatory standards and internal policies. This reduces the risk of non-compliance and fraud, minimizes manual errors, and enhances efficiency.

The process of retrieving specific data from various sources and transforming it into a usable or actionable format. In finance, this can often be extracting information from invoices and receipts. With an AI integration, data extraction and analysis can be hyper-automated.

Duplicate payments can occur when a company inadvertently pays the same invoice more than once. AI can detect and prevent duplicate payments by cross-referencing invoice data, ensuring accuracy and reducing financial loss.

In the context of B2B payments, early payment discounts are incentives suppliers offer to buyers for settling invoices before the due date. AI can identify and flag these opportunities, allowing companies to take advantage of discounts, improve cash flow, and strengthen supplier relationships.

 In accounting and finance, efficiency refers to the ability to accomplish tasks with minimal waste of time, effort, and resources. High efficiency through AP automation leads to faster processing times, reduced costs, and optimized use of financial and human resources. AP software can help increase efficiency significantly.

This refers to the complete workflow involved in handling invoices, from receipt and data extraction to approval and then payment. AI-driven end-to-end processing automates each step, ensuring accuracy, speed, and minimal human intervention.

ERP systems support various business processes in a unified system to streamline operations and improve data accuracy, for functions such as finance, accounting, human resources, and supply chain management.

This refers to seamlessly connecting ERP systems with other software solutions to optimize automation across a business process, such as integrating AI platforms for invoice processing, to enhance data flow and operational efficiency.

The use of AI and other technologies to identify and prevent fraudulent activities within financial transactions, protecting companies from financial losses and reputational damage.

This type of AI can create new content, such as text, images, or data, based on learned patterns from existing data. In finance, generative AI can be used to generate reports and predictive analytics.

Integration is the linking of various software applications to work seamlessly together, ensuring consistent data flow and reducing manual data entry. An AI integration involves incorporating new technologies with existing platforms and processes to hyper-automate an operation.

Invoice coding involves assigning relevant accounting codes to various line items on an invoice for proper categorization in financial records. Automating this process with AP software or an AI integration improves accuracy and reduces manual data entry.

The process of receiving and inputting invoices into an AP software system. Automated invoice ingestion can speed up processing times and reduce errors.

This includes the steps from receiving an invoice to recording it in the financial system and matching to correlated documents, and then making the payment. A repetitive workstream, automation can significantly enhance the efficiency and accuracy of this process.

Invoice processing automation uses AI and other technologies to handle invoice receipt, validation, and approval without manual intervention. This improves efficiency, reduces errors, and accelerates payment cycles.

LLMs are advanced AI models that are trained on vast amounts of text data. They can be used in finance for natural language processing (NLP) tasks, such as analyzing contracts or financial statements.

Machine learning in finance is the process of algorithms improving their performance over time by learning from data. It enables systems to identify patterns, make predictions, and automate processes like fraud detection and risk assessment, enhancing decision-making and efficiency.

NLP refers to using AI to understand and interpret human language in textual form. For finance and accounting, it is utilized for tasks such as analyzing financial documents, extracting contract information, and automating customer service interactions.

In the context of AI-driven invoice processing, "no-touch" refers to the ability to process and approve invoices entirely without human intervention. An AI integration automates all steps, from data extraction to final approval, enhancing efficiency and reducing errors.

OCR is a technology that converts different types of important documents, such as scanned paper documents or PDFs, into editable and searchable data. In finance, it is used to digitize invoices. OCR is a more traditional form of AP software.

Payments AI uses artificial intelligence to optimize and secure the payment process. It can identify the best times to make payments, flag early payment discount opportunities, detect fraud, and streamline transactions, enhancing overall financial efficiency.

Purchase order (PO) matching is the process of verifying that the details on an invoice align with the corresponding purchase order and delivery receipts. Automated PO matching can improve accuracy and efficiency.

Predictive analytics uses historical data and machine learning algorithms to forecast potential outcomes and future financial trends. It helps finance professionals make informed decisions, manage risks, and identify opportunities for growth.

RPA uses software robots to automate repetitive financial-process tasks, such as data entry and transaction processing, freeing human resources for more strategic work. RPA is a more traditional form of AP software.

STP refers to the automated processing of transactions from initiation to completion without manual intervention. It enhances efficiency, reduces processing time, and minimizes the risk of errors.

A workflow is the sequence of steps or processes that a financial task, such as invoice approval, follows from initiation to completion. Automating workflows with AP software or AI integration can enhance efficiency and compliance.

Vendor management is the process of overseeing and coordinating relationships with suppliers. Effective vendor management, often supported by AI, ensures timely payments, optimal pricing, and strong supplier relationships.