Finance & Accounting Index
Assesses model performance across the finance and accounting domain. Capabilities evaluated include domain-specific knowledge (accounting, investments, corporate and markets), financial analysis and reporting, compliance and audit, market research, and more.
See representative workflowsThe Artificial Analysis Finance & Accounting Index combines performance across Intelligence benchmarks sliced for finance and accounting tasks. We map common tasks from O*NET occupational classifications, then select benchmarks that represent this real-world work. Weights are derived from how often capabilities appear across those tasks.
This composite metric provides a single score for tracking model performance across finance and accounting tasks. All underlying benchmarks are run independently by Artificial Analysis. See our Intelligence Benchmarking Methodology for how evaluations are conducted.
| Capability | Weight | Evaluations |
|---|---|---|
| Business Knowledge | 30% | AA-Omniscience Business Accuracy |
| Agentic Knowledge Work | 30% | GDPval-AA v2 and AA-Briefcase |
| Reasoning | 20% | HLE |
| Agentic Tool Use | 10% | AutomationBench-AA Finance |
| Long-Context | 5% | LCR and GDP.pdf |
| Non-Hallucination | 5% | AA-Omniscience Business Non-Hallucination |
AA-Omniscience: Knowledge and Hallucination BenchmarkGDPval-AA v2 LeaderboardAA-Briefcase: Agentic Knowledge Work Benchmark
Humanity's Last Exam Benchmark Leaderboard
AutomationBench-AA: Agentic SaaS Workflow BenchmarkArtificial Analysis Long Context Reasoning Benchmark Leaderboard
GDP.pdf Benchmark LeaderboardScore
Artificial Analysis Finance & Accounting Index
Artificial Analysis Finance & Accounting Index: Capability Breakdown
Capability Breakdown
Artificial Analysis Finance & Accounting Index: Business Knowledge
Representative Workflows
Real-world workflows that exercise the capabilities the Finance & Accounting Index weights most heavily.
Example: Build a same-day EBITDA bridge for an acquisition target from five years of audited 10-Ks and an unaudited Q3 pack to reconcile GAAP and IFRS treatment, surface customer-concentration risk in the margin walk, and assemble a trading-comps table.
Example: Reconstruct twelve months of undocumented expense reimbursements from the general ledger and journal entries ahead of a SOX audit to tie each line to source evidence, produce an auditable trail, and flag unsupported items.
Example: Recover a twice-re-scoped SAP S/4HANA rollout where three departments are cross-blocked to map the critical-path dependencies, re-baseline milestones with explicit trade-offs, and draft stakeholder updates that state what slips if scope stays fixed.
Example: Reconcile two vendor studies reporting opposite consumer preferences for the same launch to compare their sampling and conjoint methodologies, explain plausible reasons for the split, and recommend the lower-risk go-to-market path.
Example: Diagnose a fulfilment centre whose pick error rate doubled after a floor reorganisation to rank likely root causes from shift logs and layout data, and propose interventions by expected lift.
Cost
Artificial Analysis Finance & Accounting Index: Cost per Task
Artificial Analysis Finance & Accounting Index vs. Cost per Task
Speed
Artificial Analysis Finance & Accounting Index: Time per Task
Output Tokens
Artificial Analysis Finance & Accounting Index: Output Tokens per Task
Release Date
Artificial Analysis Finance & Accounting Index vs. Release Date
Frequently Asked Questions
Based on the Artificial Analysis Finance & Accounting Index, the top-performing AI models for finance and accounting work are currently Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) (57), Claude Fable 5.1 (Adaptive Reasoning, Xhigh Effort, Default Fallback) (56), and GPT-6 Astra (max) (55). Rankings are updated as new models are released.
Yes. The Finance & Accounting Index from Artificial Analysis is an independent benchmark of how AI models perform on finance and accounting work. It measures performance on the finance and accounting domain, including business knowledge, agentic knowledge work, reasoning, agentic tool use, long-context analysis, and non-hallucination.
The Finance & Accounting Index is a composite benchmark from Artificial Analysis that assesses model performance across the finance and accounting domain. Capabilities evaluated include domain-specific knowledge (accounting, investments, corporate and markets), financial analysis and reporting, compliance and audit, market research, and more.
The Finance & Accounting Index is calculated as a weighted average of its capability sub-scores. The sub-scores and their weights are: Business Knowledge (30%), Agentic Knowledge Work (30%), Reasoning (20%), Agentic Tool Use (10%), Long-Context (5%), and Non-Hallucination (5%).
The Finance & Accounting Index includes AA-Omniscience Business Accuracy, GDPval-AA v2, AA-Briefcase, HLE, AutomationBench-AA Finance, LCR, GDP.pdf, and AA-Omniscience Business Non-Hallucination.
Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) currently has the highest Finance & Accounting Index score, with a score of 57 among models with published results. View model
A higher Finance & Accounting Index score indicates stronger overall performance across the benchmarks that make up the index. For a specific use case, individual benchmark results may be more informative than the composite score.