Omni-Channel Customer Onboarding with NLP-Powered Document Intelligence

Kalyan Kondisetty; Abdul Samad Mohammed; Prabhu Muthusamy

Authors

Kalyan Kondisetty Wavicle Data Solutions, USA Author
Abdul Samad Mohammed Dominos, USA Author
Prabhu Muthusamy Cognizant Technology Solutions, USA Author

Keywords:

Omni-channel onboarding, Natural Language Processing, BERT, RoBERTa, KYC automation, multilingual datasets, transformer models, banking digitization

Abstract

To enroll customers in complicated multi-channel banking ecosystems, you need smart automation for verifying and extracting unstructured documents. This study employs BERT and RoBERTa NLP models to create an omnichannel customer onboarding document intelligence platform. The suggested solution lets banks keep track of KYC paperwork, contracts, and application forms in more than one language so that they are consistent, follow the rules, and work better across all digital, branch, and contact center touchpoints. Transformer-based architectures are assessed for accuracy, recall, and F1-score using multilingual global banking datasets. Comparative testing shows that NLP-based document intelligence reduces the need for human interaction, false positives in identity verification, and the time it takes to activate an account. NLP may be able to coordinate data entry and verification to make sure that clients may safely and smoothly move from one channel to another.

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