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.
@article{arxiv.2211.06112,
title = {Towards automating Numerical Consistency Checks in Financial Reports},
author = {Lars Hillebrand and Tobias Deußer and Tim Dilmaghani and Bernd Kliem and Rüdiger Loitz and Christian Bauckhage and Rafet Sifa},
journal= {arXiv preprint arXiv:2211.06112},
year = {2022}
}
Comments
Accepted at BigData 2022, 10 pages, 3 figure, 5 tables