Accounts Payable (AP): The money a business owes to its suppliers and vendors for goods or services received.

Accounts Receivable (AR): Money owed to a business by its clients or customers for goods or services already provided.

AI (Artificial Intelligence): The simulation of human intelligence processes by machines, especially computer systems, used in finance to automate tasks, analyze data, and make predictions.

Anomaly Detection: The process of identifying unusual patterns or data points that deviate significantly from the norm, often used by AI to spot fraudulent transactions.

Audit Preparation: The process of organizing financial records and data to ensure readiness for a formal examination of financial accounts.

Automated Bookkeeping: The use of software and AI to automatically record financial transactions, categorize expenses, reconcile accounts, and update ledgers, reducing manual data entry.

Cash Flow: The movement of money into and out of a business, which impacts its liquidity.

Cash Flow Forecasting: The process of predicting a business’s future cash inflows and outflows over a specific period, often enhanced by AI analysis.

Compliance Reporting: The process of preparing and submitting financial or operational reports to regulatory bodies to demonstrate adherence to laws, regulations, and standards.

Data Security: The protection of digital data from unauthorized access, corruption, or theft, especially important for AI-driven financial tools.

Expense Management: The process of tracking, recording, and processing a business’s expenses, frequently automated by AI tools.

Financial Forecasting: Estimating future financial outcomes, like revenue and expenses, by analyzing historical data and trends, often significantly enhanced by AI.

Financial Fraud: Deceptive practices used to gain an unfair or illegal financial advantage, which AI helps detect by identifying suspicious patterns.

Hyper-Automation: The application of advanced technologies, including AI and machine learning, to automate as many business processes as possible.

Invoice Chasing: The manual process of contacting clients to remind them of overdue payments, often automated by AI tools.

Invoicing: The process of generating and sending requests for payment to clients for goods or services provided.

ISO 27001: An international standard for information security management systems (ISMS), certifying that an organization has established, implemented, maintained, and continually improved its information security.

Machine Learning (ML): A subset of AI that enables systems to automatically learn and improve from experience without being explicitly programmed, crucial for AI’s analytical capabilities in finance.

Manual Bookkeeping: The traditional method of recording financial transactions by hand in ledgers or manually entering them into software without significant automation.

Predictive Analytics: The use of historical data, statistical algorithms, and machine learning to anticipate likely future outcomes.

Real-Time Data Analysis: The processing and analysis of data as it is collected, providing immediate insights and enabling quick decision-making.

Reconciliation: The process of comparing two sets of records (e.g., bank statements and internal ledgers) to ensure they agree and to identify any discrepancies.

Semantic Keyword: A specific phrase or concept that describes the core meaning or topic of a piece of content, often used to optimize content for search engines.

Spreadsheets: Computer applications used for organizing, analyzing, and storing data in tabular form, often requiring manual entry and prone to errors in complex financial tasks.

Tax Compliance: Adherence to tax laws and regulations, including accurate calculation and timely payment of taxes, often streamlined by AI tools.