Show HN: FAB – A benchmark for AI agents doing financial due diligence (github.com)

FAB (Finance Agents Benchmark) has been launched as an open-source project aimed at evaluating large language model (LLM) agents' capabilities in conducting financial due diligence. This innovative platform features a comprehensive benchmarking system that includes 50 tasks related to a synthetic company, Meridian Industrial Supply LLC, supplemented by 160 documents and 231 grading criteria. Users can easily clone the repository from GitHub and run simulations where LLMs are tasked with analyzing financial data and generating reports, providing a standardized way to assess their performance in this specialized domain. The significance of FAB lies in its structured approach to measuring the effectiveness of AI agents in financial contexts, crucial for industries increasingly relying on autonomous decision-making tools. Initial results have shown varying task pass rates for different models, with GPT-6 Luna marking a pass rate of 50.7%. The benchmark not only facilitates the creation of more advanced financial analysis models but also opens the door for further research in improving AI reasoning and performance in complex, real-world scenarios. With its detailed grading system and extensive documentation, FAB paves the way for enhanced collaboration and innovation within the AI/ML community focused on finance.