Signature verification at branch scale for a core banking ISV
A proof of concept supported by a fully itemised production cost model of more than forty line items, giving the ISV a defensible per-branch unit cost prior to commitment.
Customer background
An Indian independent software vendor providing core banking and document imaging software to banks and financial institutions. Its customers operate large branch networks where signature verification remains a manual, high-volume task subject to data residency requirements.
Challenge
Manual signature verification was a processing bottleneck across a large branch network, and any solution was required to retain customer data within India.
Solution
Computer vision models on Amazon SageMaker scoring specimens against reference signatures, Amazon Textract for instrument capture, Amazon ECS on Fargate for the service layer, and a reviewer console for scores within the uncertainty band. Deployed entirely within the ap-south-1 Region.
Solution architecture
The engagement was delivered on the Vision Verification & Fraud Detection reference architecture, adapted to the client's data, security and operating requirements.
Reference architecture
Results and benefits
A proof of concept supported by a fully itemised production cost model of more than forty line items, giving the ISV a defensible per-branch unit cost prior to commitment.
- Computer vision verification pipeline deployed entirely within the ap-south-1 Region, satisfying data residency requirements
- Reviewer console for scores within the uncertainty band, calibrated with the ISV's risk function
- Production cost model itemised across more than forty line items, giving a defensible per-branch unit cost
- Model versioning and access logging, so every verification decision is traceable
AWS services used
About Rabbit Cloud
Rabbit Cloud is an AWS partner delivering cloud migration, platform engineering, managed operations, data platforms and AI/ML solutions for enterprises and software companies. Engagements are delivered by senior engineering teams to the AWS Well-Architected Framework, with security, compliance and cost governance addressed from the initial architecture.
Client identity withheld under a confidentiality agreement; identifying detail has been generalised.
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