الملخص
Multi-party financial chatrooms are vital for sales-and-trading professionals, but their complexity makes manual recovery of missed trades infeasible: each Request for Quote (RFQ) is an event whose final price and trade outcome appear many messages after the RFQ-trigger message (the inquiry message), interleaved with concurrent RFQs from other participants. We cast this as event extraction (EE) over multi-party dialogue and present FinDialogLens, a hybrid LLM pipeline in which compact fine-tuned classifiers act as inference-time scaffolds: they detect RFQ-triggers and price/trade outcome metadata, an RFQ-Level Module segments per-event RFQ windows, and a Trade Engine fills argument roles. With GPT-4o, FinDialogLens reaches 92.1% and 94.3% accuracy on final price and trade outcome, respectively, outperforming full-chatroom CoT prompting methods; fine-tuned open-source LLMs with as few as 3B parameters achieve comparable performance with modest in-domain data. To make the LLM-based solution practical at scale, a difficulty-aware router balances cost and accuracy by allocating RFQs between a low-cost rule-based engine and the higher-performing LLM-powered Trade Engine, cutting LLM calls by 85% on final price while recovering half of the accuracy gap to FinDialogLens (GPT-4o), saving over $300/day at our 70,000-RFQ/day scale.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Fu, C. L., Ni, H., & Madahian, B. (2026). FinDialogLens: Event Extraction over Multi-Party Dialogue for Missed-Trade Identification in Financial Chatrooms. https://omanscience.com/ar/articles/findialoglens-event-extraction-over-multi-party-dialogue-for-missed-trade-identification-in-financial-chatrooms
MLA 9
Fu, Chin-Lun, et al. "FinDialogLens: Event Extraction over Multi-Party Dialogue for Missed-Trade Identification in Financial Chatrooms." https://omanscience.com/ar/articles/findialoglens-event-extraction-over-multi-party-dialogue-for-missed-trade-identification-in-financial-chatrooms.
شيكاغو (المؤلف–التاريخ)
Fu, Chin-Lun, Hong Ni, and Behrouz Madahian. 2026. "FinDialogLens: Event Extraction over Multi-Party Dialogue for Missed-Trade Identification in Financial Chatrooms." https://omanscience.com/ar/articles/findialoglens-event-extraction-over-multi-party-dialogue-for-missed-trade-identification-in-financial-chatrooms.
هارفارد
Fu, C. L., Ni, H. and Madahian, B. (2026) 'FinDialogLens: Event Extraction over Multi-Party Dialogue for Missed-Trade Identification in Financial Chatrooms', Available at: https://omanscience.com/ar/articles/findialoglens-event-extraction-over-multi-party-dialogue-for-missed-trade-identification-in-financial-chatrooms.
فانكوفر
Fu CL, Ni H, Madahian B. FinDialogLens: Event Extraction over Multi-Party Dialogue for Missed-Trade Identification in Financial Chatrooms. https://omanscience.com/ar/articles/findialoglens-event-extraction-over-multi-party-dialogue-for-missed-trade-identification-in-financial-chatrooms
IEEE
C. L. Fu, H. Ni, and B. Madahian, "FinDialogLens: Event Extraction over Multi-Party Dialogue for Missed-Trade Identification in Financial Chatrooms," https://omanscience.com/ar/articles/findialoglens-event-extraction-over-multi-party-dialogue-for-missed-trade-identification-in-financial-chatrooms.