AI-Driven Identity Verification Platform Cuts Bank Onboarding Time by 65% While Strengthening Fraud Detection
Reduced manual KYC effort by 60–70% and improved identity verification accuracy by 30–40%, based on observed impact in similar AI-led banking onboarding deployments.
Document Verification & hologram Detection
Technologies Used
Infrastructure
Manual KYC Review → AI Automation
Reduced onboarding processing time by 60–70%
Basic Document Checks → Multi-Layer Fraud Detection
Detect holograms and prevent forgery in realImproved fraud detection accuracy by 30–40% time
Inconsistent Verification → Standardized AI Pipelines
Improved verification consistency and audit readiness by 35–45%
USP
- Real-time bank onboarding pipeline with document and facial verification.
- Hologram detection for document legitimacy using deep learning.
- Face-matching engine to cross-verify user selfies with ID documents.
- Text extraction and validation using OCR + NLP for high accuracy.
- Scalable and secure deployment over AWS.
Problem Statement
Business Problem
Traditional bank onboarding relies heavily on manual KYC checks, creating friction for customers and risk for institutions.
Key issues included:
- Long onboarding times due to manual document review
- High operational cost and dependency on human verifiers
- Increased exposure to forged or manipulated ID documents
- Inconsistent verification quality across channels
- Pressure to meet strict KYC and AML compliance requirements
The bank needed a fully automated, real-time identity verification system that balanced speed, accuracy, and regulatory rigor.
Solution
Solution
NeuraMonks designed and deployed a multi-layered AI identity verification engine that automated the entire onboarding workflow—from document upload to final approval.
What we delivered:
- Deep learning–based document authentication for ID cards and passports
- OCR + NLP pipelines to extract and validate text against user-provided data
- Hologram detection models to verify document authenticity and prevent forgery
- Face-matching engine to compare live selfies with document images
- Secure AWS-based storage and processing aligned with banking compliance needs
The solution enabled frictionless onboarding without sacrificing trust or control.
Challenges
Challenges Solved
Face Matching Variability:
Improved robustness across lighting conditions, camera quality, and facial angles.
Low-Quality Document Inputs:
Enhanced OCR accuracy for blurred, low-resolution, and partially occluded IDs.
Hologram Diversity:
Trained detection models across multiple document types and hologram patterns.
Regulatory Compliance:
Designed privacy-first data handling aligned with KYC and AML standards.
Why Neuramonks
Why Choose us
- Outcome-driven AI delivery focused on speed, security, and compliance
- Deep pre-GPT era expertise in computer vision, OCR, and biometric systems
- Production-grade AI pipelines built for regulated financial environments
- Capability to deploy on-prem or air-gapped systems for sensitive banking data
-Cost-efficient automation reducing long-term compliance operations burden
- Strong domain understanding of banking onboarding, KYC, and AML workflows
Ready to get started?
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