AI-Powered KYC Verification

GenAI

Onboarding

KYC

Risk

Efficiency

Top Contributor

KYC Expert

Approved

Submitted over 1 year ago

4.7

105 Votes

Rank #3

350 Points

Business Problem

Manual KYC is slow, error-prone, and costly, leading to poor customer experience and high operational overhead.

Use Case / Solution

Automate identity verification using facial recognition against government databases/selfies. Extract and validate data from uploaded documents (passports, driving licenses, utility bills) using OCR and NLP. Cross-reference data points for consistency. Flag potential discrepancies for manual review.

Detailed Description

This project aims to fully automate the Know Your Customer (KYC) process for new retail banking customers. By leveraging AI, we can significantly reduce the time taken for verification from days to minutes, minimize manual errors, and enhance fraud detection capabilities. The system will involve a user-friendly interface for document upload and selfie capture, backend AI models for processing, and an admin dashboard for reviewing flagged cases.

AI / GenAI Application

Computer Vision for facial recognition and liveness detection. OCR for text extraction from documents. NLP for named entity recognition (NER) and data validation (e.g., address format, date validity). Potentially a simple ML model to assess document authenticity based on visual features.

Technology Stack:

Python, OpenCV, TensorFlow/PyTorch, spaCy, AWS Rekognition, AWS Textract, React, Next.js

Attachments

Idea Details

ID:20240519-0001

Department:Retail Banking

Type:Process Improvement

Patent Status:Filed

Visibility:Public

AI Generated Summary

This approved Retail Banking idea proposes an AI-driven KYC automation system using Computer Vision, OCR, and NLP via technologies like TensorFlow, spaCy, and AWS AI services. It aims to cut onboarding time, reduce errors, and lower operational costs by automating ID and document verification.

Team