FinTrust: A Comprehensive Benchmark of Trustworthiness Evaluation in
  Finance Domain
Recent LLMs have demonstrated promising ability in solving finance related
problems. However, applying LLMs in real-world finance application remains
challenging due to its high risk and high stakes property. This paper
introduces FinTrust, a comprehensive benchmark specifically designed for
evaluating the trustworthiness of LLMs in finance applications. Our benchmark
focuses on a wide range of alignment issues based on practical context and
features fine-grained tasks for each dimension of trustworthiness evaluation.
We assess eleven LLMs on FinTrust and find that proprietary models like o4-mini
outperforms in most tasks such as safety while open-source models like
DeepSeek-V3 have advantage in specific areas like industry-level fairness. For
challenging task like fiduciary alignment and disclosure, all LLMs fall short,
showing a significant gap in legal awareness. We believe that FinTrust can be a
valuable benchmark for LLMs' trustworthiness evaluation in finance domain.
68f59eb88589920bf4d3211b
Tiansheng Hu
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2025-10-20T12:11:04.076Z
67492b9e347c3876f22b3684
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Tiansheng Hu
user
HughieHu
68f59eb88589920bf4d3211c
Tongyan Hu
claimed_verified
2025-10-20T12:11:00.964Z
66e83ec5deb449d8d856e78d
/avatars/c5e56be65fcacb3192ce10ba6d8f48e2.svg
Tongyan Hu
user
entropyhu
68f59eb88589920bf4d3211d
Liuyang Bai
68f59eb88589920bf4d3211e
Yilun Zhao
68f59eb88589920bf4d3211f
Arman Cohan
68f59eb88589920bf4d32120
Chen Zhao
FinTrust: A Comprehensive Benchmark of Trustworthiness Evaluation in
  Finance Domain
Recent LLMs have demonstrated promising ability in solving finance related
problems. However, applying LLMs in real-world finance application remains
challenging due to its high risk and high stakes property. This paper
introduces FinTrust, a comprehensive benchmark specifically designed for
evaluating the trustworthiness of LLMs in finance applications. Our benchmark
focuses on a wide range of alignment issues based on practical context and
features fine-grained tasks for each dimension of trustworthiness evaluation.
We assess eleven LLMs on FinTrust and find that proprietary models like o4-mini
outperforms in most tasks such as safety while open-source models like
DeepSeek-V3 have advantage in specific areas like industry-level fairness. For
challenging task like fiduciary alignment and disclosure, all LLMs fall short,
showing a significant gap in legal awareness. We believe that FinTrust can be a
valuable benchmark for LLMs' trustworthiness evaluation in finance domain.
FinTrust is a benchmark designed to evaluate the trustworthiness of LLMs in finance applications, focusing on alignment issues and revealing gaps in legal awareness.
LLMs FinTrust trustworthiness alignment issues safety industry-level fairness fiduciary alignment disclosure legal awareness