10 Best AI Tools in Excel for Finance in 2025
Excel is a critical tool in finance, supporting financial modeling and operations across various sectors. Below are some AI tools that enhance Excel's functionality in finance.
Excel is a critical tool in finance, supporting financial modeling and operations across various sectors. Below are some AI tools that enhance Excel's functionality in finance.
Embedded as an Excel add-in for seamless workflow integration. Supported by OpenAI. Auditable workflows with in-line references, trace, and undo features. Direct integration with public financial data sources like CapIQ, VisibleAlpha, FactSet, and SEC filings. Strong encryption and security practices.
Limited general availability; evolving features and documentation. Requires analyst input for edge cases in financial models.
Use Cases: Building and auditing financial models such as DCF, LBO, and P&L.
Natural-language prompts for formula explanation and chart creation. Integration with Microsoft 365 for governance and storage. Assists in ratio analysis and data exploration.
Requires specific licensing and IT enablement. Outputs are drafts requiring analyst validation. Limited capability for complex models.
Use Cases: Quick data analysis and formula initiation.
Interactive dashboards from Excel data with automatic refresh. Row-level security for controlled data access. Combines Excel models with live feeds from various data sources.
Requires separate licensing and setup. Complex version control with Excel sources.
Use Cases: Portfolio KPI dashboards and interactive presentations.
Spreadsheet-native planning with data model integration. Familiar grid experience for analysts. Versioning and audit history for governance.
Not designed for custom financial modeling. Best suited for standardized planning and reporting.
Excel is a critical tool in finance, supporting financial modeling and operations across various sectors.
Use Cases: Portfolio forecasting and KPI rollups.
No/low-code ETL for data cleaning and transformation. Combines multiple datasets into a single structure. Reusable workflows for efficiency.
Requires separate application and governance. Learning curve for building and maintaining data flows.
Use Cases: Data normalization and repeatable data-to-model pipelines.
Formula-driven data pulls for financials and estimates. Streamlines data gathering and updates. Templates for faster workbook creation.
Requires specific licensing and coverage. Feeds data but requires manual model design.
Use Cases: Market snapshots and scheduled data refreshes.
Financial and transaction data retrieval through Excel functions. Comprehensive data coverage for private equity needs. One-click data refresh for live updates.
Requires entitlements and desktop Excel for optimal use. Consistency in data fields depends on analyst standardization.
Use Cases: LBO input gathering and transaction comps.
Excel add-in for financial consolidation and reporting. Automates board packs and management reporting. Maintains Excel as the primary interface.
Primarily for FP&A, not for deal-team financial modeling. More effective with ERP/GL connectors.
Use Cases: Portfolio monitoring and multi-entity rollups.
Focus on private markets data integration. Vendor templates and training for quick productivity. Supports thematic work and sponsor mapping.
Overlap with other tools; requires coordinated coverage. Sanity-check critical items due to potential data gaps.
Use Cases: Deal sourcing and sector analysis.
AI-driven extraction of structured tables from SEC filings into Excel. Facilitates quarterly updates and comps maintenance. Beneficial during earnings season for model updates.
Footnotes and non-GAAP items require manual analysis. Reconciliation to source documents is necessary.
Use Cases: Public-comps updates and financial tab creation.
Based on reporting by TechBullion.