Large Language Models (LLMs) are reshaping consumer decision-making, particularly in communication with firms, yet our understanding of their impact remains limited. This research explores the effect of LLMs on consumer complaints submitted to the Consumer Financial Protection Bureau from 2015 to 2024, documenting the adoption of LLMs for drafting complaints and evaluating the likelihood of obtaining relief from financial firms. We analyzed over 1 million complaints and identified a significant increase in LLM usage following the release of ChatGPT. We find that LLM usage is associated with an increased likelihood of obtaining relief from financial firms. To investigate this relationship, we employ an instrumental variable approach to mitigate endogeneity concerns around LLM adoption. Although instrumental variables suggest a potential causal link, they cannot fully capture all unobserved heterogeneity. To further establish this causal relationship, we conducted controlled experiments, which support that LLMs can enhance the clarity and persuasiveness of consumer narratives, thereby increasing the likelihood of obtaining relief. Our findings suggest that facilitating access to LLMs can help firms better understand consumer concerns and level the playing field among consumers. This underscores the importance of policies promoting technological accessibility, enabling all consumers to effectively voice their concerns.

翻译：大型语言模型（LLMs）正在重塑消费者的决策过程，尤其是在与企业的沟通过程中，然而我们对其影响的理解仍然有限。本研究探讨了LLMs对2015年至2024年间提交至消费者金融保护局的消费者投诉的影响，记录了消费者使用LLMs起草投诉的采纳情况，并评估了从金融机构获得救济的可能性。我们分析了超过100万份投诉，发现在ChatGPT发布后，LLM的使用显著增加。我们发现，LLM的使用与从金融机构获得救济的可能性增加相关。为了探究这一关系，我们采用工具变量法来缓解围绕LLM采纳的内生性问题。尽管工具变量暗示了潜在的因果关系，但它们无法完全捕捉所有未观测到的异质性。为了进一步确立这种因果关系，我们进行了对照实验，实验支持LLMs能够提高消费者叙述的清晰度和说服力，从而增加获得救济的可能性。我们的研究结果表明，促进LLMs的获取可以帮助企业更好地理解消费者的关切，并拉平消费者之间的竞争环境。这凸显了促进技术可及性政策的重要性，使所有消费者都能有效地表达他们的关切。