arXiv cs.AI· Daniel Rupawalla·· 14 小时前AI 评分38
Bank-World:评估智能体银行工作流能力的基准
Bank-World: A Benchmark for Evaluating Agents on Banking Workflows
AI 导读
Bank-World 是一个包含 50 项银行任务、覆盖两家模拟机构的基准,通过单轮任务与多轮交互测试智能体在记录核对、权限获取、交易执行和状态报告一致性上的表现。四个模型共 1,600 次尝试中,正确决策常未能转化为完成的工作:智能体重复收费、在收款人之间错误分配正确总额、在审批未完成时执行付款。Sol 单轮完成率领先,Opus 多轮完成率最高,Grok 成功的多轮任务更多但稳定性较差。
正文 · 原文
Abstract:Bank-World is a benchmark of 50 banking tasks across two simulated institutions. Completing banking work requires more than producing the right calculation: agents must reconcile records, obtain permission, execute transactions, and keep instructions and status reports consistent as circumstances change. Bank-World tests these requirements through single-turn assignments and multi-turn interactions with simulated employees who supply information, approve actions, and revise instructions. Grading combines executable checks of recorded actions and state with model judgments of task requirements, including whether valid alternative solutions satisfy them. Across 1,600 attempts by four models, we find that correct decisions often fail to become completed work. Agents charge fees twice, distribute the correct total in incorrect amounts among the recipients, and execute payments while approval is pending. Their strengths also differ: Sol leads single-turn completion, Opus has the highest observed multi-turn completion rate, and Grok succeeds across more multi-turn tasks but less consistently. Bank-World makes these differences inspectable through task-level results and worked examples connecting source evidence, agent decisions, and simulated consequences. We retain the task environments, executable graders, and full trajectories privately to reduce contamination and preserve the benchmark for future evaluations.
| Comments: | 43 pages, 3 figures, including appendices. Ancillary files contain the task ID mapping, reward specifications, and single-turn check-authority mapping |
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.39733 [cs.AI] |
| (or arXiv:2610.39733v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.39733 arXiv-issued DOI via DataCite |
Submission history
From: Daniel Rupawalla [view email]
[v1]
Thu, 29 Oct 2026 09:59:39 UTC (88 KB)
来源:arXiv cs.AI · arxiv.org