ML-Powered Banking Intent Prediction for Travel Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Financial institutions lack the ability to anticipate the banking functions customers intend to perform at their branches or ATMs, leading to unnecessary customer travel, resource utilization, and increased carbon emissions.
Innovation Solution
A method using a machine learning model integrated with a map application on a mobile device to determine the user's intended function at a financial institution or ATM, providing options such as online execution, appointment scheduling, and eco-friendly travel alternatives, and prepping the institution for the customer's visit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the financial institution provides traditional in-branch services, then customers can perform banking functions, but customers must travel to the branch causing carbon emissions and time loss
Solution Approach 1:
The patent creates virtual copies of banking services through mobile applications and online platforms, allowing customers to perform transactions remotely. This digital replication eliminates the need for physical travel to branches, thereby reducing carbon emissions while maintaining service accessibility
Solution Approach 2:
The patent introduces digital intermediaries (mobile apps, online banking platforms, and automated systems) between customers and banking services. These intermediaries enable remote interaction with banking functions, eliminating the need for customers to physically travel to branches and thus reducing carbon footprint
2Adaptability or versatility
If the financial institution does not know customer intentions, then all customer requests can be handled, but resources are inefficiently utilized and wait times increase
Solution Approach 1:
The patent implements systems that analyze customer data, behavior patterns, and transaction histories to predict and prepare for customer needs before arrival. By performing preliminary actions such as pre-processing transactions, preparing resources, and anticipating service requirements, the system optimizes resource allocation and reduces wait times while maintaining versatility in handling various banking functions
3Ease of operation
If customers travel to the destination, then banking functions can be performed, but time is lost including waiting for representative availability
Solution Approach 1:
The patent replaces mechanical systems requiring physical presence (in-branch transactions with human representatives) with automated digital systems. Mobile applications, online platforms, and automated teller machines handle transactions without requiring customer travel or waiting for representative availability, thereby eliminating time loss while maintaining full banking functionality
4Loss of information
If the machine learning model analyzes past user interactions, then the intended function can be determined, but system complexity increases
Solution Approach 1:
The patent implements a universal machine learning framework that handles multiple types of customer interactions and predicts various banking functions through a single multi-functional system. This approach consolidates complexity into one versatile model rather than requiring separate systems for different functions, making the complexity management more efficient while improving intent recognition
Data Source
AI summary
Methods, apparatuses and non-transitory media are provided for receiving, via a data sharing communication from a map application executing on a mobile computing device, and via an application on the mobile computing device associated with a user, map application data. The map application data may include a destination. The methods, apparatus and non-transitory media may be further provided for determining, by a machine learning model and based on the received map application data, a function that the user intends to perform at the destination, the machine learning model analyzing past user interactions with an entity associated with the destination, and, based on determining the function the user intends to perform, generating a notification, in the application, of one or more options for performing the function.