Case Study: Rabobank boosts audit anomaly detection with KNIME

How Rabobank got 300 auditors to run anomaly detection independently

Rabobank, a Dutch multinational banking and financial services company, needed a better way to detect money laundering patterns in audit. Its challenge was to move beyond sample-based testing and help auditors identify both known and unknown suspicious behaviors across the full population of data, while building stronger data literacy across a largely non-technical audit team. KNIME was used as the analytics platform to support this shift.

KNIME implemented reusable workflows for anomaly detection, data inspection, visualization, and exporting results, allowing 300 auditors to run analyses independently without needing deep technical expertise. Rabobank trained its auditors to use KNIME and embedded the tool into its audit operating model, helping create a more data-driven culture. The program scaled from 7 use cases in the first year to 57 in 2020, significantly expanding the use of data analytics in audit.

Rabobank