Case Study: Leading Global Auditor Company achieves 30% reduction in comfort letter review time with EdgeVerve AI Next

EdgeVerve AI Next helps a leading global auditor reduce comfort letter review time by 30%

Leading Global Auditor Company faced a slow, highly manual process to review roughly 650 comfort letters annually, which required over 12,600 hours of auditor effort to search, extract and reconcile critical clauses across multiple document types. To tackle this challenge, they engaged EdgeVerve and implemented EdgeVerve AI Next’s Document AI capability.

EdgeVerve automated extraction, reconciliation and comfort labeling using NLP, computer vision and machine learning, ingesting PDFs and producing labeled PDFs and Excel workbooks while enabling keyword/intent/entity search and risk profiling. The EdgeVerve solution reduced review time by 30%, increased extraction/reconciliation accuracy to about 80%, cut research effort by 90%, and delivered a 10x productivity improvement for the auditing and underwriting teams.