Case Study: CACEIS (asset servicing bank) achieves faster, more accurate analysis of large financial data with ProcessMaker IDP

How CACEIS analyzes large quantities of financial data with machine learning through ProcessMaker IDP

CACEIS, the asset-servicing banking group owned by Crédit Agricole and Santander with €4.6 trillion in custody and €2.4 trillion under administration, serves asset managers, insurers, pension funds and other institutional clients worldwide. As it scaled, CACEIS faced a surge of incoming data—much of it unstructured—and found that roughly 80% of information still required manual vetting, creating a bottleneck while they tried to maintain exacting data quality standards and clearer cost reporting for clients.

By deploying ProcessMaker IDP’s machine‑learning document processing, CACEIS automated extraction from unstructured sources (images, PDFs, emails, forms, presentations), allowing analysts to review and correct inaccuracies far more efficiently. The result is faster, more accurate data analysis, cleaner client reports, stronger cost transparency and benchmarking, and improved relationships with asset managers and trustees.

Caceis

Scott Foster

Product Specialist