Towards automating Numerical Consistency Checks in Financial Reports
We introduce KPI-Check, a novel system that automatically identifies and cross-checks semantically equivalent key performance indicators (KPIs), e.g. “revenue” or “total costs”, in real-world German financial reports. It combines a financial named entity and relation extraction module with a BERT-based filtering and text pair classification component to extract KPIs from unstructured sentences before linking them to synonymous occurrences in the balance sheet and profit & loss statement. The tool achieves a high matching performance of 73.00% micro F1 on a hold out test set and is currently being deployed for a globally operating major auditing firm to assist the auditing procedure of financial statements.
- Published in:
Big Data Conference Europe - Type:
Inproceedings - Authors:
Hillebrand, Lars; Deußer, Tobias; Dilmaghani, Tim; Kliem, Bernd; Loitz, Rüdiger; Bauckhage, Christian; Sifa, Rafet - Year:
2022
Citation information
Hillebrand, Lars; Deußer, Tobias; Dilmaghani, Tim; Kliem, Bernd; Loitz, Rüdiger; Bauckhage, Christian; Sifa, Rafet: Towards automating Numerical Consistency Checks in Financial Reports, Big Data Conference Europe, 2022, https://arxiv.org/abs/2211.06112, Hillebrand.etal.2022a,
@Inproceedings{Hillebrand.etal.2022a,
author={Hillebrand, Lars; Deußer, Tobias; Dilmaghani, Tim; Kliem, Bernd; Loitz, Rüdiger; Bauckhage, Christian; Sifa, Rafet},
title={Towards automating Numerical Consistency Checks in Financial Reports},
booktitle={Big Data Conference Europe},
url={https://arxiv.org/abs/2211.06112},
year={2022},
abstract={We introduce KPI-Check, a novel system that automatically identifies and cross-checks semantically equivalent key performance indicators (KPIs), e.g. "revenue" or "total costs", in real-world German financial reports. It combines a financial named entity and relation extraction module with a BERT-based filtering and text pair classification component to extract KPIs from unstructured sentences...}}
