Case Study: Leading Global Investment Bank achieves faster compliance risk analysis with Sigmoid

Automating financial crime compliance analysis for a leading investment bank

Sigmoid worked with a leading global investment bank that needed to automate compliance risk analysis to meet stricter financial crime compliance requirements. The bank’s existing Excel-based process was manual, slow, and difficult to scale across divisions, with additional challenges from low-quality data, legacy systems, and an inconsistent batch framework.

Sigmoid implemented an automated risk scoring solution that consolidated data from more than 30 sources into a central pipeline using Java, Hadoop, IBM Db2, Spring Boot, and Elasticsearch. The new framework standardized ETL and batch processing, calculated high/medium/low risk scores, and surfaced results through customer profile portals. As a result, Sigmoid reduced risk assessment time from 3 days to 1 hour, enabled near real-time anomaly flagging, and lowered operational costs by 1.5x.