FinBoardBench: Benchmarking Dynamic Wealth Management and Strategic Financial Reasoning of LLMs via Board Game Simulations
Researchers have developed FinBoardBench, a new evaluation suite designed to test the dynamic financial reasoning and wealth management capabilities of large language models (LLMs). The suite utilizes three classic board games: Cashflow, Acquire, and Monopoly, to assess skills such as cash flow management, investment forecasting, and negotiation. Experiments with nine advanced LLMs showed that while they possess basic planning abilities, they struggle with complex interactions and dynamic decision-making, often prioritizing asset acquisition over liquidity and becoming vulnerable to financial crises. AI
IMPACT This benchmark could reveal critical limitations in LLMs' real-world financial decision-making, guiding future development towards more robust and adaptable AI agents.