The 5th Financial Narrative Processing Workshop (FNP 2023)

To be held at the 2023 IEEE International Conference on Big Data (IEEE BigData 2023), Sorrento, Italy, from 15 to 18 December 2023.

 

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Provisional Dates:

  • 1st Call for workshop papers: May 15, 2023
  • 2nd Call for workshop papers: August 15, 2023
  • Final Call for workshop papers: October 1, 2023
  • Due date for workshop papers submission: October 30, 2023 (anywhere in the world). 
  • Notification of paper acceptance to authors: November 12, 2023
  • Camera-ready of accepted papers: November 20, 2023
  • Workshop date:  1 day event : December 15-18, 2023 (exact date to be announced)

Workshop Description:

Financial narrative processing is an emerging field that combines natural language processing (NLP) and machine learning (ML) techniques to extract, summarise, and analyse both qualitative and quantitative financial data. As the amount of financial data continues to grow exponentially, this data is increasingly considered as big data, which presents challenges and opportunities for data scientists.

The 5th Financial Narrative Processing Workshop (FNP 2023) aims to bring together researchers and industry practitioners to share their latest research results and practical experiences in financial narrative processing, which is a key aspect of big data. In particular, the workshop will focus on three shared tasks: Financial Narrative Summarization, Financial Table of Content Extraction, and Financial Causality Detection. These tasks will challenge participants to apply state-of-the-art techniques in NLP and ML to extract meaningful insights from financial documents. The workshop will provide an informal and vibrant forum for discussion and collaboration, with the goal of advancing the field of financial narrative processing within the context of big data. We welcome submissions from researchers and practitioners in academia and industry.

FNP 2023 workshop is organised by a team of experts who have been at the forefront of financial NLP research for the past five years. We have organised more than 7 international events, introduced NLP and AI shared tasks, and provided big datasets and methodologies needed to push forward the emerging field of financial NLP.  Our workshop series has contributed significantly to the field of financial NLP, as evidenced by our proceedings on ACL anthology and citations in Google Scholar.

We are also expanding to cover more languages where we introduced two new languages, Spanish and Greek, in addition to the original English and French datasets in the last edition of FNP. In 2022 our workshop was sponsored by the European Language Resources Association (ELRA), as well as AI Pioneer Companies: Yseop and Fortia who provided free registration and prizes to the shared task winners. We will expand our datasets and tasks to include new challenges in financial narrative processing.

Previous Proceedings

* All FNP proceedings across the years are on ACL Anthology: https://aclanthology.org/venues/fnp/. The 1st FNP was associated with LREC 2018 http://lrec-conf.org/workshops/lrec2018/W27/pdf/book_of_proceedings.pdf 

FNP Google Scholar: https://scholar.google.com/citations?hl=en&user=8Qn7yJ8AAAAJ 

Motivation and Topics of Interest:

Financial narrative disclosures represent a significant portion of firms’ overall financial communications with investors. Textual commentaries help to clarify issues that may be obscured by complex accounting methods and footnote disclosures. In addition, narratives summarise corporate strategy, contextualise results, explain governance arrangements, describe corporate social responsibility policy, and provide forward-looking information for investors. However, financial narratives may also provide management with an opportunity to obfuscate accounting results and manipulate readers’ perceptions of underlying economic performance.

In the previous FNP workshop, we organised a panel of experts to discuss the future of Financial NLP and data leaders from AI firms in France and London. The consensus was that financial data has increased exponentially in recent years due to the increase in regulations. This has led to an increase in the number of financial news surrounding the events of releasing such disclosures. Therefore, state-of-the-art methodologies are necessary to understand and analyse huge and sensitive financial data in a short amount of time.

We believe that the FNP 2023 workshop will continue to contribute to the field of Financial NLP by providing a platform for researchers and industry practitioners to share their research results and practical development experiences in Big Data research, development, and practice. In addition, our workshop will help participants gain a better understanding of the challenges posed by big data and its 5 V’s (velocity, volume, value, variety, and veracity) in financial text analysis.

Topic of Interest in Relation to Financial NLP

We encourage research on topics related to analyzing financial narratives using state-of-the-art NLP techniques, including but not limited to morphological analysis, disambiguation, tokenization, part-of-speech tagging, named entity recognition, chunking, parsing, semantic role labeling, sentiment analysis, document quality, and advanced readability metrics. The use of NLP and machine learning in the financial domain has encouraged studies around gender and ethnicities imbalance, as well as mental health and well-being research.

Given the focus of the IEEE Big Data 2023 conference, we also encourage research on under-resourced languages and under-represented financial markets. In recent years, FNP has included research on Arabic, Spanish, and Portuguese financial markets. Our collaboration with the MultiLing workshop (http://multiling.iit.demokritos.gr) has highlighted the importance of summarization across domains and sources that are related to finance (e.g., company blogs, product reviews, market briefs, etc.). This includes financial multilingual and cross-lingual summarization using single-document summarization, multi-document summarization, summarization evaluation, headline generation, and cross-domain/cross-topic summarization.

Given the international nature of the event, we particularly welcome FNP papers reporting non-English and multilingual research, describing the different regulatory regimes within which companies operate internationally. We are introducing Spanish and Greek financial datasets in addition to the current English and French datasets in FNP 2022.

Shared Tasks

FNP-FNS 2023 shared tasks:

  1. Financial Narrative Summarisation (FNS 2023): summarise financial data in three languages: English, Spanish and Greek.  
  2. Financial Table of Content Extraction (FinTOC 2023): detect structure of financial documents in three languages: English, French and Spanish. 
  3. Financial Causality Detection (FinCausal 2023): detect causes and effects in financial disclosures in English and Spanish.

For more details about the shared tasks please visit: http://wp.lancs.ac.uk/cfie/shared-tasks/

Organising Committee:

Call For Papers

We invite papers describing original, completed or ongoing, unpublished research in Financial Natural Language Processing and Financial Text Analysis. As financial data is increasingly considered as big data, we encourage submissions that address the five main and innate characteristics of big data (velocity, volume, value, variety, and veracity) in the context of financial narrative processing.

We encourage submissions on topics that include, but are not limited to, the following:

  • Applying core technologies on financial narratives within the context of big data: morphological analysis, disambiguation, tokenization, part-of-speech tagging, named entity recognition, chunking, parsing, semantic role labelling, sentiment analysis, document quality and advanced readability metrics, etc.
  • Using NLP to detect misreporting in relation to diversity and well-being on issues related to gender, ethnicity, women at work as well as employee mental health and stability, in the context of big data.
  • Financial narrative resources and tools for managing and analysing large-scale financial data.
  • Summarization techniques across domains and sources that are related to finance (e.g. company blogs, product reviews, market briefs, etc.). This includes financial multilingual and cross-lingual summarization using single-document summarization, multi-document summarization, summarization evaluation, headline generation, cross-domain/cross-topic summarization.
  • Analysis of Online Social Networks for detection of public opinions towards financial events.
  • Multilingual analysis, describing the different regulatory regimes within which companies operate internationally.
  • Ongoing research and preliminary results that explore the intersection of financial narrative processing and big data.
  • Negative results, for example, techniques and methodologies that work for certain languages but not on others. Other venues could be showing that state-of-the-art technologies such as BERT could fail on certain tasks or languages.

All papers accepted will be included in the conference proceedings published by the IEEE Computer Society Press.

Paper Submission Instructions:

We follow IEEE submission format. Please submit a full paper (up to 10 page IEEE 2-column format) or short paper (up to 4 page IEEE 2-column format) through the online submission system.

Click here to submit your paper: https://wi-lab.com/cyberchair/2023/bigdata23/scripts/ws_submit.php

Anti-Harassment Policy:
The workshop supports the ACL anti-harassment policy.

Programme Committee:

  • Andrew Moore (Lancaster University, UK)
  • Antonio Moreno Sandoval (UAM, Spain)
  • Vasiliki Athanasakou (SMU, Canada)
  • Doaa Samy (Cairo University, Egypt and LLI-UAM, Spain)
  • Blanca Carbajo Coronado (UAM, Spain)
  • Aris Kosmopoulos (NCSR, Demokritos),
  • Ahmed AbuRa’ed (Universitat Pompeu Fabra, Spain), 
  • Nikiforos Pittaras (NCSR, Demokritos).
  • Denys Proux (Naver Labs, Switzerland)
  • George Giannakopoulos (SKEL Lab – NCSR Demokritos, Greece)
  • Houda Bouamor (CMU, Qatar)
  • Mahmoud El-Haj (SCC, Lancaster University, UK)
  • Marina Litvak (Sami Shamoon College of Engineering, Israel)
  • Irina Rabaev (Sami Shamoon College of Engineering, Israel)
  • Natalia Vanetik (Sami Shamoon College of Engineering, Israel)
  • Martin Walker (University of Manchester, UK)
  • Paul Rayson (SCC, Lancaster University, UK)
  • Sira Ferradans, France
  • Dialekti Valsamou (Fortia Financial Solutions, France)
  • Ismail El Maarouf (Imprevicible, France)
  • Steven Young (LUMS, Lancaster University, UK) 
  • Mohan Subbiah (LUMS, Lancaster University, UK)
  • Paulo Alves (Accounting, Universidade Católica Portuguesa, Portugal)
  • Thomas Schleicher (MBA, Manchester University)
  • Ana Gisbert (Accounting, UAM, Spain)
  • John M. Conroy (IDA Center for Computing Sciences, USA)
  • Elena Lloret (University of Alicante, Spain)
  • Vangelis Karkaletsis (NCSR Demokritos)
  • Mark Last (Ben-Gurion University of the Negev, Israel)
  • George Petasis (NCSR Demokritos, Greece)
  • Peter Rankel (Elder Research Inc., USA)
  • Remi Juge (Fortia Financial Solutions, France)
  • Dominique Mariko (Yseop, France)
  • Anubhav Gupta (Yseop, France)
  • Hanna Abi-Akl (Yseop, France)
  • Hugues de Mazancourt (Yseop, France)
  • Estelle Labidurie (Yseop, France)
  • Stephane Durfort(Yseop, France)