@article{zavitsanos2025calibrating,title={Calibrating TabTransformer for financial misstatement detection},author={Zavitsanos, Elias and Kelesis, Dimitrios and Paliouras, Georgios},year={2025},journal={Applied Intelligence},publisher={Springer},volume={55},number={1},pages={3},}
ACM
Machine Learning for Identifying Risk in Financial Statements: A Survey
The work herein reviews the scientific literature on Machine Learning approaches for financial risk assessment using financial reports. We identify two prominent use cases that constitute fundamental risk factors for a company, namely misstatement detection and financial distress prediction. We further categorize the related work along four dimensions that can help highlight the peculiarities and challenges of the domain. Specifically, we group the related work based on (a) the input features used by each method, (b) the sources providing the labels of the data, (c) the evaluation approaches used to confirm the validity of the methods, and (d) the machine learning methods themselves. This categorization facilitates a technical overview of risk detection methods, revealing common patterns, methodologies, significant challenges, and opportunities for further research in the field.
@article{10.1145/3723157,title={Machine Learning for Identifying Risk in Financial Statements: A Survey},author={Zavitsanos, Elias and Spyropoulou, Eirini and Giannakopoulos, George and Paliouras, Georgios},year={2025},month=mar,journal={ACM Comput. Surv.},publisher={Association for Computing Machinery},address={New York, NY, USA},doi={10.1145/3723157},issn={0360-0300},url={https://doi.org/10.1145/3723157},note={Just Accepted},keywords={risk assessment, misstatement detection, financial distress, bankruptcy prediction, fraud detection, financial reports, financial statements, machine learning, data mining, auditing},}
2024
ICAIF
Bankruptcy Prediction: Data Augmentation, LLMs and the Need for Auditor’s Opinion
@inproceedings{sideras2024bankruptcy,title={Bankruptcy Prediction: Data Augmentation, LLMs and the Need for Auditor's Opinion},author={Sideras, Andreas and Bougiatiotis, Konstantinos and Zavitsanos, Elias and Paliouras, Georgios and Vouros, George},year={2024},booktitle={Proceedings of the 5th ACM International Conference on AI in Finance},pages={453--460},}
Nature
Entrant: A large financial dataset for table understanding
@article{zavitsanos2024entrant,title={Entrant: A large financial dataset for table understanding},author={Zavitsanos, Elias and Mavroeidis, Dimitris and Spyropoulou, Eirini and Fergadiotis, Manos and Paliouras, Georgios},year={2024},journal={Scientific Data},publisher={Nature Publishing Group UK London},volume={11},number={1},pages={876},}
LREC
Dice@ ml-esg-3: Esg impact level and duration inference using llms for augmentation and contrastive learning
In Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing@ LREC-COLING 2024, Mar 2024
@inproceedings{bougiatiotis2024dice,title={Dice@ ml-esg-3: Esg impact level and duration inference using llms for augmentation and contrastive learning},author={Bougiatiotis, Konstantinos and Sideras, Andreas and Zavitsanos, Elias and Paliouras, Georgios},year={2024},booktitle={Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing@ LREC-COLING 2024},pages={234--243},}
2023
CNA
Efficient Complex Network Representation Using Prime Numbers
@inproceedings{bougiatiotis2023efficient,title={Efficient Complex Network Representation Using Prime Numbers},author={Bougiatiotis, Konstantinos and Paliouras, Georgios},year={2023},booktitle={International Conference on Complex Networks and Their Applications},pages={75--86},organization={Springer},}
IEEE
Identifying going concern issues in auditor opinions: link to bankruptcy events
@inproceedings{bougiatiotis2023identifying,title={Identifying going concern issues in auditor opinions: link to bankruptcy events},author={Bougiatiotis, Konstantinos and Zavitsanos, Elias and Paliouras, Georgios},year={2023},booktitle={2023 IEEE International Conference on Big Data (BigData)},pages={2805--2813},organization={IEEE},}
FNS
The Financial Narrative Summarisation Shared Task (FNS 2023)
Elias Zavitsanos, Aris Kosmopoulos, George Giannakopoulos, Marina Litvak, Blanca Carbajo-Coronado, Antonio Moreno-Sandoval, and Mo El-Haj
In 2023 IEEE International Conference on Big Data (BigData), Mar 2023
@inproceedings{zavitsanos2023financial,title={The Financial Narrative Summarisation Shared Task (FNS 2023)},author={Zavitsanos, Elias and Kosmopoulos, Aris and Giannakopoulos, George and Litvak, Marina and Carbajo-Coronado, Blanca and Moreno-Sandoval, Antonio and El-Haj, Mo},year={2023},booktitle={2023 IEEE International Conference on Big Data (BigData)},pages={2890--2896},organization={IEEE},}
2022
ACL
FiNER: Financial numeric entity recognition for XBRL tagging
@inproceedings{loukas2022finer,title={FiNER: Financial numeric entity recognition for XBRL tagging},author={Loukas, Lefteris and Fergadiotis, Manos and Chalkidis, Ilias and Spyropoulou, Eirini and Malakasiotis, Prodromos and Androutsopoulos, Ion and Paliouras, Georgios},year={2022},month=may,booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},publisher={Association for Computational Linguistics},address={Dublin, Ireland},pages={4419--4431},doi={10.18653/v1/2022.acl-long.303},url={https://aclanthology.org/2022.acl-long.303/},}
2021
EACL
Regulatory compliance through Doc2Doc information retrieval: A case study in EU/UK legislation where text similarity has limitations
@article{chalkidis2021regulatory,title={Regulatory compliance through Doc2Doc information retrieval: A case study in EU/UK legislation where text similarity has limitations},author={Chalkidis, Ilias and Fergadiotis, Manos and Manginas, Nikolaos and Katakalou, Eva and Malakasiotis, Prodromos},year={2021},journal={arXiv preprint arXiv:2101.10726},}
NAACL
Paragraph-level rationale extraction through regularization: A case study on European court of human rights cases
@article{chalkidis2021paragraph,title={Paragraph-level rationale extraction through regularization: A case study on European court of human rights cases},author={Chalkidis, Ilias and Fergadiotis, Manos and Tsarapatsanis, Dimitrios and Aletras, Nikolaos and Androutsopoulos, Ion and Malakasiotis, Prodromos},year={2021},journal={arXiv preprint arXiv:2103.13084},}
ECONLP
EDGAR-CORPUS: Billions of tokens make the world go round
@article{loukas2021edgar,title={EDGAR-CORPUS: Billions of tokens make the world go round},author={Loukas, Lefteris and Fergadiotis, Manos and Androutsopoulos, Ion and Malakasiotis, Prodromos},year={2021},journal={arXiv preprint arXiv:2109.14394},}
ICAIF
Financial misstatement detection: a realistic evaluation
@inproceedings{zavitsanos2021financial,title={Financial misstatement detection: a realistic evaluation},author={Zavitsanos, Elias and Mavroeidis, Dimitris and Bougiatiotis, Konstantinos and Spyropoulou, Eirini and Loukas, Lefteris and Paliouras, Georgios},year={2021},booktitle={Proceedings of the Second ACM International Conference on AI in Finance},pages={1--9},}
2020
EMNLP
LEGAL-BERT: The muppets straight out of law school
@article{chalkidis2020legal,title={LEGAL-BERT: The muppets straight out of law school},author={Chalkidis, Ilias and Fergadiotis, Manos and Malakasiotis, Prodromos and Aletras, Nikolaos and Androutsopoulos, Ion},year={2020},journal={arXiv preprint arXiv:2010.02559},}
Dice@ ml-esg-3: Esg impact level and duration inference using llms for augmentation and contrastive learningIn Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing@ LREC-COLING 2024, Mar 2024