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.

Citation information

Hillebrand, Lars; Deußer, Tobias; Dilmaghani, Tim; Kliem, Bernd; Loitz, Rüdiger; Bauckhage, Christian; Sifa, Rafet: Towards automating Numerical Consistency Checks in Financial Reports, 2022 IEEE International Conference on Big Data (Big Data), 2022, https://www.computer.org/csdl/proceedings-article/big-data/2022/10020308/1KfRFDJVlbq, Hillebrand.etal.2022a,

Associated Lamarr Researchers

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Prof. Dr. Christian Bauckhage

Director to the profile
Prof. Dr. Rafet Sifa

Prof. Dr. Rafet Sifa

Principal Investigator Hybrid ML to the profile