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A Hybrid AI Tool to Extract Key Performance Indicators from Financial Reports for Benchmarking

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Christin PüntAuthors Info & Claims

DocEng '19: Proceedings of the ACM Symposium on Document Engineering 2019

Article No.: 36, Pages 1 - 4

https://doi.org/10.1145/3342558.3345420

Published: 23 September 2019 Publication History

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Abstract

We present a tool that enables benchmarking of companies by means of automatic extraction of key performance indicators from publicly available financial reports. Our tool monitors companies of interest so that their reports are automatically downloaded as soon as they become available. After tables and paragraphs have been extracted from the documents using a table detection module based on convolutional neural networks, relevant key performance indicators are stored in a central database. The extracted values are finally displayed in a user-friendly web application where the user can compare time series of key performance indicators against arbitrary available companies.

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References

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Iwashokun OAde-Ibijola A(2024)Parsing of Research Documents into XML Using Formal GrammarsApplied Computational Intelligence and Soft Computing10.1155/2024/66713592024Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1155/2024/6671359
Deußer TAli SHillebrand LNurchalifah DJacob BBauckhage CSifa R(2022)KPI-EDGAR: A Novel Dataset and Accompanying Metric for Relation Extraction from Financial Documents2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)10.1109/ICMLA55696.2022.00254(1654-1659)Online publication date: Dec-2022
https://doi.org/10.1109/ICMLA55696.2022.00254
Ramamurthy RLubbering MBell TGebauer MUlusay BUedelhoven DKhameneh TLoitz RPielka MBauckhage CSifa R(2021)Automatic Indexing of Financial Documents via Information Extraction2021 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI50451.2021.9659977(01-05)Online publication date: 5-Dec-2021
https://doi.org/10.1109/SSCI50451.2021.9659977
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Published In

DocEng '19: Proceedings of the ACM Symposium on Document Engineering 2019

September 2019

254 pages

ISBN:9781450368872

DOI:10.1145/3342558

General Chairs:
Uwe Borghoff,
Sonja Schimmler

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGDOC: ACM Special Interest Group for Design of Communications

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Association for Computing Machinery

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Published: 23 September 2019

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DocEng '19: ACM Symposium on Document Engineering 2019

September 23 - 26, 2019

Berlin, Germany

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DocEng '19 Paper Acceptance Rate 30 of 77 submissions, 39%;

Overall Acceptance Rate 194 of 564 submissions, 34%

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Iwashokun OAde-Ibijola A(2024)Parsing of Research Documents into XML Using Formal GrammarsApplied Computational Intelligence and Soft Computing10.1155/2024/66713592024Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1155/2024/6671359
Deußer TAli SHillebrand LNurchalifah DJacob BBauckhage CSifa R(2022)KPI-EDGAR: A Novel Dataset and Accompanying Metric for Relation Extraction from Financial Documents2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)10.1109/ICMLA55696.2022.00254(1654-1659)Online publication date: Dec-2022
https://doi.org/10.1109/ICMLA55696.2022.00254
Ramamurthy RLubbering MBell TGebauer MUlusay BUedelhoven DKhameneh TLoitz RPielka MBauckhage CSifa R(2021)Automatic Indexing of Financial Documents via Information Extraction2021 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI50451.2021.9659977(01-05)Online publication date: 5-Dec-2021
https://doi.org/10.1109/SSCI50451.2021.9659977
Zemnickis JNiedrite LKozmina N(2020)A Little Bird Told Me: Discovering KPIs from Twitter DataDatabases and Information Systems10.1007/978-3-030-57672-1_13(161-175)Online publication date: 12-Aug-2020
https://doi.org/10.1007/978-3-030-57672-1_13

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