Strengthening Customer Data Accuracy in the Banking Sector with ML-Based Deduplication

Duplicate and fragmented customer records create major challenges in banking, affecting compliance, fraud prevention, onboarding efficiency, and customer experience. This case study shows how AI & ML improved Data Accuracy through intelligent Banking MDM and Customer Data Deduplication. By using ML-based matching across branches, online apps, credit card systems, and legacy platforms, the solution created a trusted golden customer record, reduced duplicates to under 2%, accelerated onboarding by 3X, lowered operational effort by 75%, and delivered $1M+ in annual savings.