• Use CaseAgentic AI in Finance

  Agentic AI in treasury: cash visibility and autonomous liquidity moves

  Treasury teams are moving past static reporting into agentic AI systems that monitor cash positions in real time, recommend FX hedges, and execute intraday liquidity moves within defined guardrails. This deep dive maps the use cases, the architectural requirements, and the questions treasury leaders should be asking before they hand an agent any execution authority.

• InsightAgentic AI in Finance

  Agentic AI for finance teams: autonomous workflows from close to forecast

  Autonomous AI agents are moving into the finance function—handling reconciliations, drafting variance commentary, and maintaining rolling forecasts without waiting for human prompts. This piece examines where agentic workflows are production-ready today, where the risk of removing human judgment is too high, and what finance leaders need to evaluate before deploying.

• InsightAgentic AI in Finance

  AI in Finance: 20 Use Cases Across Record-to-Report, Order-to-Cash, and Procure-to-Pay

  A buyer-oriented map of twenty AI use cases in finance, organized by the three core process taxonomies — record-to-report, order-to-cash, and procure-to-pay — with the vendor archetypes that address each.

• Use CaseAgentic AI in Finance

  AI Expense Auditing: Policy Violations, Duplicates, and Outliers

  This guide examines how AI-driven tools identify policy violations, duplicate claims, and anomalous expenses in corporate finance operations. It offers practical considerations for integrating AI into existing expense auditing workflows.

• ComparisonAgentic AI in Finance

  AI-Powered Financial Planning: Forecasting, Scenario Modeling, and Variance Analysis

  This insight analyzes AI-driven financial planning tools focusing on forecasting accuracy, scenario modeling flexibility, and variance analysis capabilities. It assesses solutions from vendors such as Anaplan, Workday Adaptive Planning, and Oracle, guiding finance leaders on selecting technologies that meet enterprise requirements.

• ToolAgentic AI in Finance

  Finance AI ROI Calculator

  Calculate the potential return on investment for deploying AI in accounts payable automation and fraud mitigation, factoring in processing improvements, error rates, and operational costs.

• Lexicon entryAgentic AI in Finance

  Reconciliation

  AI-driven account reconciliation leverages anomaly detection and matching algorithms to reduce manual effort and improve accuracy. Enterprise deployments show up to 60% reduction in reconciliation time by automating transaction matching. Key considerations include data quality, integration with ERP systems, and explainability of detected anomalies.

• ComparisonAgentic AI in Finance

  Vic.ai vs. Tipalti vs. Coupa: AI Accounts Payable Automation

  This comparison examines Vic.ai, Tipalti, and Coupa to evaluate their AI-driven accounts payable automation capabilities. The analysis covers AI features, integration options, cost structures, and enterprise suitability to aid financial decision-makers.