Proximity Detection for Bank Customer Service Automation
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Solution Overview
Problem
Existing bank customer service systems face challenges in efficiently managing in-person transactions at bank branches, often resulting in long lines, insufficient staff, and burdensome processes for customers.
Innovation Solution
A system that detects the physical proximity of bank customers using sensors and computing devices, identifies customer profiles, and sends check-in prompts to guide customers through available banking transactions, thereby streamlining the service process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional in-person bank service is provided, then customers can conduct face-to-face transactions, but long customer lines and extended wait times occur
Solution Approach 1:
The system performs preliminary actions by detecting customer proximity via sensors before the customer reaches the service area, automatically identifying the customer profile, and pre-preparing service information. This advance preparation eliminates the need for customers to wait in line, as the system has already initiated the service process before the customer physically arrives at the counter.
Solution Approach 2:
The system enables self-service by automatically detecting customers, retrieving their profiles, and presenting relevant transaction options without requiring customer initiation or manual check-in. The customer simply needs to approach the bank, and the system autonomously guides them through available transactions, reducing both wait time and operational complexity.
2Productivity
If more bank personnel are deployed to reduce wait times, then customer service speed improves, but operational costs increase
Solution Approach 1:
The system replaces human staff with an automated sensor-based detection and identification system. Sensors continuously monitor for customer presence, automatically retrieve customer profiles from databases, and present service options without requiring bank personnel to manually check in each customer or review their accounts, thereby maintaining high productivity with reduced staffing requirements.
Solution Approach 2:
The patent substitutes mechanical human labor with an automated electronic system comprising sensors, computing devices, and database systems. The sensor network detects customer presence, the computing device processes identification and retrieves profiles, and the system presents transaction options—completely replacing the manual processes previously requiring bank tellers or customer service representatives for initial customer intake.
3Reliability
If manual customer check-in process is used, then customer identity verification is achieved, but the process becomes burdensome and time-consuming
Solution Approach 1:
The system performs automatic customer identification and verification without requiring any manual action from the customer. The sensor detects the customer's approach, the computing device automatically queries the customer profile database using detected identifiers (such as mobile device signals or biometric data), and retrieves verified customer information, making the entire verification process transparent and effortless for the customer.
Solution Approach 2:
The patent replaces manual identity verification procedures with an automated electronic identification system. Sensors detect customer presence and capture identifying information, computing devices automatically query databases to verify customer profiles, and the system cross-references data without human intervention, thereby maintaining high verification reliability while eliminating the burden of manual check-in forms or interactions.
Data Source
AI summary
The present disclosure relates to a system, method, and mobile computing device apparatus for detecting the physical presence of a bank customer at a bank branch, and delivering an enhanced customer service experience by anticipating the bank customer's needs. Detection of the bank customer through visual data such as facial recognition, or electronic data such as medium range electronic communication networks to the customer's mobile computing device, allow a bank to retrieve relevant customer profile and customer transaction history data and use that data to deliver communications to the customer even before the customer speaks to a bank teller.