mlsanityData to 14 Oct 2026

FinTeam: A Multi-Agent Collaborative Intelligence System for Comprehensive Financial Scenarios

arXiv 2507.10448 ↗First posted 5 Jul 2025cs.CE cs.LGcited by 5

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

Financial report generation tasks range from macro- to micro-economics analysis, also requiring extensive data analysis. Existing LLM models are usually fine-tuned on simple QA tasks and cannot comprehensively analyze real financial scenarios. Given the complexity, financial companies often distribute tasks among departments. Inspired by this, we propose FinTeam, a financial multi-agent collaborative system, with a workflow with four LLM agents: document analyzer, analyst, accountant, and consultant. We train these agents with specific financial expertise using constructed datasets. We evaluate FinTeam on comprehensive financial tasks constructed from real online investment forums, including macroeconomic, industry, and company analysis. The human evaluation shows that by combining agents, the financial reports generate from FinTeam achieved a 62.00% acceptance rate, outperforming baseline models like GPT-4o and Xuanyuan. Additionally, FinTeam's agents demonstrate a 7.43% average improvement on FinCUGE and a 2.06% accuracy boost on FinEval. Project is available at https://github.com/FudanDISC/DISC-FinLLM/.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 23 of its 32 references that are in the map. First posted on arXiv 5 Jul 2025.

Builds on

23 of 32 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design23 Nov

Other references · 22

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  3. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  4. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,724
  5. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
  6. 2023BloombergGPT: A Large Language Model for Financecited by 939
  7. 2013Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Textscited by 310
  8. 2023PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Financecited by 222
  9. 2024MDAgents: An Adaptive Collaboration of LLMs for Medical Decision-Makingcited by 163
  10. 2024A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalistcited by 137
  11. 2024AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulatorcited by 101
  12. 2023DISC-MedLLM: Bridging General Large Language Models and Real-World Medical Consultationcited by 90
10 more
  1. 2023Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Casescited by 86
  2. 2023InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuningcited by 82
  3. 2023DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuningcited by 64
  4. 2023BBT-Fin: Comprehensive Construction of Chinese Financial Domain Pre-trained Language Model, Corpus and Benchmarkcited by 60
  5. 2023ZeRO++: Extremely Efficient Collective Communication for Giant Model Trainingcited by 52
  6. 2023FinEval: A Chinese Financial Domain Knowledge Evaluation Benchmark for Large Language Modelscited by 52
  7. 2021Multilingual and Cross-Lingual Intent Detection from Spoken Datacited by 35
  8. 2023FinVis-GPT: A Multimodal Large Language Model for Financial Chart Analysiscited by 28
  9. 2024Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Taskscited by 23
  10. 2025Multi-Agent Simulator Drives Language Models for Legal Intensive Interactioncited by 22

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.

  1. 2025FinSight: Towards Real-World Financial Deep Researchcited by 9
  2. 2026RealFin: How Well Do LLMs Reason About Finance When Users Leave Things Unsaid?cited by 9
  3. 2026Harnessing Generalist Agents for Contextualized Time Seriescited by 3
  4. 2026Beyond Isolated Behaviors: Hierarchical User Modeling for LLM Personalizationcited by 1
  5. 2026FinSAgent: Corpus-Aligned Multi-Agent RAG Framework for Evidence-Grounded SEC Filing Question Answeringcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models
  2. 2024FinTeamExperts: Role Specialized MOEs For Financial Analysis
  3. 2026OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents
  4. 2026FinReasoning: A Hierarchical Benchmark for Reliable Financial Research Reporting
  5. 2026Toward Expert Investment Teams:A Multi-Agent LLM System with Fine-Grained Trading Tasks
  6. 2025Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoning
  7. 2024FinVision: A Multi-Agent Framework for Stock Market Prediction
  8. 2025FinDebate: Multi-Agent Collaborative Intelligence for Financial Analysis