@inproceedings{dos-santos-2026-scripted,
title = "Scripted Hesitation in a Financial Customer-Service Chatbot: A {B}razilian {P}ortuguese Case Study",
author = "dos Santos, Valeria Vieira",
editor = "Huang, Jimin and
Lee, Yongjae and
Ananiadou, Sophia and
Chen, Hsin-Hsi and
Takamura, Hiroya and
Chen, Chung-Chi",
booktitle = "Proceedings of the 11th Workshop on Financial Technology and Natural Language Processing",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.finnlp-1.2/",
pages = "10--14",
ISBN = "979-8-89176-466-8",
abstract = "Financial customer service is a high-stakes conversational domain in which debt negotiation, cancellations, and complaints require pragmatic resources beyond fluent text generation. We present a case study of linguistic hesitation in approximately 3,000 WhatsApp customer-service interaction records (approximately 89k tokens) from one Brazilian financial company, contrasting clients, human agents, and one commercial scripted chatbot. A rule-based pipeline adapted a Conversation Analysis typology to written chat and identified 20,938 pattern occurrences across four formal categories. Client messages account for 59{\%} of detections, but unavailable per-role token totals preclude rate comparisons. Archived within-role distributions place 40{\%} of agent detections in sensitive contexts and 50{\%} of chatbot detections in technical contexts. The chatbot also relies on only 3{--}5 recurrent surface forms. We interpret these results as descriptive evidence that human and scripted hesitation serve different interactional profiles, not as a general claim about financial chatbots or LLM-based agents. The study illustrates both the value of pragmatic analysis for financial conversational systems and the limits of conclusions drawn from a single-company, single-annotator corpus."
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%0 Conference Proceedings
%T Scripted Hesitation in a Financial Customer-Service Chatbot: A Brazilian Portuguese Case Study
%A dos Santos, Valeria Vieira
%Y Huang, Jimin
%Y Lee, Yongjae
%Y Ananiadou, Sophia
%Y Chen, Hsin-Hsi
%Y Takamura, Hiroya
%Y Chen, Chung-Chi
%S Proceedings of the 11th Workshop on Financial Technology and Natural Language Processing
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-466-8
%F dos-santos-2026-scripted
%X Financial customer service is a high-stakes conversational domain in which debt negotiation, cancellations, and complaints require pragmatic resources beyond fluent text generation. We present a case study of linguistic hesitation in approximately 3,000 WhatsApp customer-service interaction records (approximately 89k tokens) from one Brazilian financial company, contrasting clients, human agents, and one commercial scripted chatbot. A rule-based pipeline adapted a Conversation Analysis typology to written chat and identified 20,938 pattern occurrences across four formal categories. Client messages account for 59% of detections, but unavailable per-role token totals preclude rate comparisons. Archived within-role distributions place 40% of agent detections in sensitive contexts and 50% of chatbot detections in technical contexts. The chatbot also relies on only 3–5 recurrent surface forms. We interpret these results as descriptive evidence that human and scripted hesitation serve different interactional profiles, not as a general claim about financial chatbots or LLM-based agents. The study illustrates both the value of pragmatic analysis for financial conversational systems and the limits of conclusions drawn from a single-company, single-annotator corpus.
%U https://aclanthology.org/2026.finnlp-1.2/
%P 10-14
Markdown (Informal)
[Scripted Hesitation in a Financial Customer-Service Chatbot: A Brazilian Portuguese Case Study](https://aclanthology.org/2026.finnlp-1.2/) (dos Santos, FinNLP 2026)
ACL