Ilias Zavitsanos

2025

1. Springer

   

   Calibrating TabTransformer for financial misstatement detection

   Elias Zavitsanos, Dimitrios Kelesis, and Georgios Paliouras

   Applied Intelligence, Feb 2025

   Bib PDF

   @article{zavitsanos2025calibrating,
     title = {Calibrating TabTransformer for financial misstatement detection},
     author = {Zavitsanos, Elias and Kelesis, Dimitrios and Paliouras, Georgios},
     year = {2025},
     month = feb,
     journal = {Applied Intelligence},
     publisher = {Springer},
     volume = {55},
     number = {1},
     pages = {3},
   }

2. ACM

   

   Machine Learning for Identifying Risk in Financial Statements: A Survey

   Elias Zavitsanos, Eirini Spyropoulou, George Giannakopoulos, and Georgios Paliouras

   ACM Comput. Surv., Mar 2025

   Just Accepted

   Abs DOI Bib

   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

1. ICAIF

   

   Bankruptcy Prediction: Data Augmentation, LLMs and the Need for Auditor’s Opinion

   Andreas Sideras, Konstantinos Bougiatiotis, Elias Zavitsanos, Georgios Paliouras, and George Vouros

   In Proceedings of the 5th ACM International Conference on AI in Finance, Nov 2024

   Bib PDF Code Website

   @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},
     month = nov,
   }

2. Nature

   

   Entrant: A large financial dataset for table understanding

   Elias Zavitsanos, Dimitris Mavroeidis, Eirini Spyropoulou, Manos Fergadiotis, and Georgios Paliouras

   Scientific Data, Aug 2024

   Bib PDF Code

   @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},
     month = aug,
     journal = {Scientific Data},
     publisher = {Nature Publishing Group UK London},
     volume = {11},
     number = {1},
     pages = {876},
   }

3. LREC

   

   Dice@ ml-esg-3: Esg impact level and duration inference using llms for augmentation and contrastive learning

   Konstantinos Bougiatiotis, Andreas Sideras, Elias Zavitsanos, and Georgios Paliouras

   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, May 2024

   Bib PDF

   @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},
     month = may,
     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

1. IEEE

   

   Identifying going concern issues in auditor opinions: link to bankruptcy events

   Konstantinos Bougiatiotis, Elias Zavitsanos, and Georgios Paliouras

   In 2023 IEEE International Conference on Big Data (BigData), Dec 2023

   Bib PDF Code

   @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},
     month = dec,
     booktitle = {2023 IEEE International Conference on Big Data (BigData)},
     pages = {2805--2813},
     organization = {IEEE},
   }

2. 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), Dec 2023

   Bib PDF

   @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},
     month = dec,
     booktitle = {2023 IEEE International Conference on Big Data (BigData)},
     pages = {2890--2896},
     organization = {IEEE},
   }

2021

1. ICAIF

   

   Financial misstatement detection: a realistic evaluation

   Elias Zavitsanos, Dimitris Mavroeidis, Konstantinos Bougiatiotis, Eirini Spyropoulou, Lefteris Loukas, and Georgios Paliouras

   In Proceedings of the Second ACM International Conference on AI in Finance, May 2021

   Bib PDF

   @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},
     month = may,
     booktitle = {Proceedings of the Second ACM International Conference on AI in Finance},
     pages = {1--9},
   }