Automated Customer Enrollment via Mobile OCR and Validation

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Solution Overview

Problem

Current methods for customer enrollment in financial institutions are inefficient and costly, requiring manual operations that can lead to errors and increased costs.

Innovation Solution

An automated system using mobile communication devices that employs OCR, machine learning-based classifiers, and rule engines to extract and validate personal identifying information from identification documents, generating a customer profile and facilitating account creation through a series of SMS requests and responses or web-based applications.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual operations are used for customer enrollment, then flexibility and human judgment are maintained, but operational efficiency decreases and errors increase

Engineering Contradiction:

Improveoperational efficiencyVSAvoidmanual operations

Core Design Contradiction:

ProductivityVSExtent of automation

Solution Approach 1:

The system enables customers to complete enrollment themselves through automated processes. The mobile communication device captures identification documents, the system automatically extracts personal information via OCR, validates it against KYC requirements, and creates customer profiles without requiring manual intervention from enrollment staff.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical processes are replaced with automated electronic systems. The patent uses optical character recognition (OCR) to replace manual data entry, machine learning classifiers to replace manual verification, and automated rule engines to replace manual compliance checking, thereby eliminating manual operations while maintaining accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated systems are implemented, then operational efficiency improves, but system complexity increases

Engineering Contradiction:

Improveoperational efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The complex enrollment system is divided into distinct functional modules: document capture module, optical character recognition module, information extraction module, validation module, and customer profile generation module. Each module handles a specific task independently, making the overall complex system manageable and easier to implement through a series of coordinated automated steps.

Inventive Principle:

Principle #1Segmentation

3Measurement precision

If manual data entry is used, then flexibility in handling edge cases is maintained, but error rates increase and time consumption increases

Engineering Contradiction:

Improvedata accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

Manual data entry and verification are replaced with automated optical character recognition (OCR) and machine learning classifiers. The system automatically extracts personal identifying information from identification documents, validates it against predefined KYC requirements, and generates customer profiles, thereby eliminating human errors while reducing time consumption compared to manual processes.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This system improves customer satisfaction and operational efficiency by automating the enrollment process, reducing manual errors and costs, while ensuring compliance with KYC requirements through validated customer profiles.

Implementation Method 1

The customer enrollment application may then prompt (operation 128) the potential customer to acquire an image of his or her identification document (130) (e.g., using the camera of the mobile communication device)

Methodology Applied

Scientific EffectPhotography: Photography

Implementation Method 2

The information extraction may involve performing optical character recognition (OCR) of the identification document image in order to extract one or more textual strings

Methodology Applied

Scientific EffectOptical character recognition:

Data Source

PatentUS20200250766A1Automated customer enrollment using mobile communication devices

Publication Date: 2020.08.06 TEACHERS INSURANCE & ANNUITY ASSOC OF AMERICA

AI summary

Disclosed are methods and systems for automated customer enrollment using mobile communication devices. An example method includes: receiving, by a computer system, an identification document image produced by a mobile communication device; extracting, from the identification document image a personal identifying information item; computing a confidence score of the personal identifying information item; responsive to determining that the confidence score meets or exceeds a confidence threshold, creating a customer profile for a person identified by the identification document, wherein the customer profile comprises the personal identifying information item; and supplying the customer profile to a financial account creation workflow.