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Problem Statement: Signature matching is a time-consuming and error-prone process when done manually. Organizations need a reliable and efficient method for signature extraction and matching to reduce errors and increase productivity.

Our AI-Based Solution: Signature matching is vital in digital banking onboarding, automating verification for KYC compliance, reducing errors, and enhancing efficiency. It prevents fraud, ensures data accuracy, and enables regulatory adherence. Furthermore, it empowers data analysis for fraud detection and customer insights, optimizing decision-making. Integrating signature matching strengthens digital banking operations, security, and customer trust.

Result: Our solution simplifies the process of signature extraction and matching, reducing the time and effort required to perform these tasks manually. By leveraging AI-based technology, we have increased the accuracy and reliability of signature matching, resulting in better outcomes for organizations.

Machine Learning Models: Yolo8, Auto-encoder for Cleaning, and VGG (Visual Geometry Group) Neural Network for Signature Matching.

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