FinNLP 2026 — The 11th Workshop on Financial Technology and Natural Language Processing

About

The FinNLP workshop, as the annual event of ACL SIG-FinTech, focuses on applying NLP, Machine Learning, and Large Language Models to finance, economics, and law, aiming to drive interdisciplinary innovation and address unique challenges in these fields. Since 2019, FinNLP has served as a bridge between AI and NLP communities by collocating with major conferences. Its proceedings are available on the ACL Anthology.

FinNLP addresses the complexities of financial documents, which often contain tables and diverse multimodal data, as well as legal and compliance challenges in the financial industry. Key workshop topics include financial language modeling, multi-modal and graph representation learning, conversational agents, financial search and question answering, event discovery, compliance, and responsible AI practices in finance and law.

We have several interesting shared tasks in the collocated event, FinEval. Please refer to the Call for Challenges for more details.

// For Researchers

Call for Papers →

Long, short, and demo paper submissions. Published in the ACL Anthology.

// For Practitioners

Call for Challenges →

FinEval shared tasks — datasets, baselines, and leaderboards.

Topics of Interest

We invite submissions of original contributions on methods, theories, applications, and systems on artificial intelligence, machine learning, natural language processing & understanding, big data, statistical learning, data analytics, and deep learning, with a focus on knowledge discovery in the financial services domain. The scope of the workshop includes, but is not limited to, the following areas:

Language modeling on financial corpora, including tabular and numerical data, and multi-modal modeling
Graph representation learning and mining on financial data
Multi-source knowledge integration and fusion
Synthetic and genuine financial datasets and benchmarks
Transfer learning applications for financial data
Financial search and question answering systems
Event discovery and impact on organizational equity price
ESG event discovery, evaluation, and impact assessment
Compliance monitoring
Cross-disciplinary LLM-based methodologies for financial and legal domains
Applications of LLMs in financial auditing and regulatory reporting
Ethical implications and bias mitigation in AI applications
Hallucination mitigation and evaluation in LLMs
Privacy concerns and data protection strategies
Enhancing interpretability and explainability of LLM models
Responsible AI practices and governance
Methods, evaluation metrics, benchmarks, and datasets for LLMs in finance and law

Important Dates

Submission Deadline	TBD
Submission System	TBD
Paper Notification	TBD
Camera-Ready Deadline	TBD
FinNLP-2026 @ EMNLP	October 24–29, 2026
Location	Budapest, Hungary

// All deadlines are Anywhere on Earth (AoE)

Submission

Format

The ACL Template MUST be used for your submission(s). Accepted papers' proceedings will be published at the ACL Anthology.

Long Paper: up to 8 pages of content, plus unlimited pages for references and appendix.
Short Paper and Demo Paper: up to 4 pages of content, plus unlimited references and appendix.

Review & Presentation

The reviewing process will be double-blind for Long and Short Paper, and single-blind for Demo Paper.
Submissions must be in electronic form using the paper submission link above.
At least one author of each accepted paper should register and present their work at FinNLP 2026.

Open Research Policy

As part of ACL SIG-FinTech's reproducibility and transparency initiative, we will pilot an open research policy for accepted papers.

Authors of accepted papers are strongly encouraged to publicly release their implementation code, model inputs, and model outputs to support reproducibility and future re-evaluation.
For LLM-based approaches, authors are encouraged to release prompts, inference configurations, generated outputs, and evaluation artifacts associated with their experiments whenever possible.
Exceptions may be granted in cases involving legal, licensing, privacy, commercial, or security constraints. Authors requesting exceptions should discuss their situation with the organizers.
Presentation videos from the workshop will be uploaded to the ACL SIG-FinTech YouTube channel for public access and long-term educational use.