AR Assistant for Transaction Object Identification and Financing
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Solution Overview
Problem
Traditional financing processes for expensive items are cumbersome and time-consuming, often deterring individuals from making purchases due to the complexity of loan applications.
Innovation Solution
An augmented reality (AR) system that captures images of objects using a portable device, identifies them through machine learning, and provides context data including loan options, allowing users to negotiate and initiate loan transactions within the AR interface, with point data stored on a distributed ledger network for secure tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional loan application processes are used, then financing can be obtained, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The system performs preliminary actions by capturing images of the object and pre-calculating loan terms before the user even applies. The AR interface displays loan information upfront, allowing users to see financing options immediately rather than waiting through a lengthy application process.
Solution Approach 2:
The system enables self-service by allowing users to obtain financing information and initiate loan applications autonomously through the AR interface. Users can view loan terms, compare options, and apply without requiring extensive manual processing by loan officers, thereby reducing both time and complexity.
2Reliability
If traditional loan application processes are used, then financing can be obtained, but the complexity of the process increases
Solution Approach 1:
The system merges multiple functions into a single integrated AR interface: object identification, context data retrieval, loan term calculation, and application initiation all occur within one unified interface. This consolidation eliminates the need for users to navigate through multiple separate systems and procedures.
Solution Approach 2:
The AR interface acts as an intermediary that simplifies the complex loan application process. It translates complex financial terms into easily understandable information displayed in the AR view, and mediates between the user and the loan processing system by pre-validating information and guiding users through necessary steps.
3Ease of operation
If immediate access to loan information is provided, then user convenience is improved, but system complexity increases
Solution Approach 1:
The system replaces traditional mechanical information retrieval methods with automated image recognition and AI-based loan calculation systems. The camera captures the object, AI algorithms instantly identify it and retrieve relevant loan information, and the AR interface automatically displays personalized loan terms without requiring manual data entry or complex user navigation.
Solution Approach 2:
The system performs preliminary calculations of loan terms based on the identified object and user profile before the user even requests information. This pre-computation allows immediate display of accurate loan information, enhancing user convenience while the complexity is managed through automated backend processing.
Data Source
AI summary
Techniques are described for capturing an image of a physical object, and presenting the image in an augmented reality (AR) user interface (UI) with an overlay that includes context information regarding physical object in the image. An application running on a portable computing device receives an object image captured using the device camera. The application, and/or a remote service, analyzes the image to identify the object. Context data describing the object is determined and presented through the application's AR UI. The AR UI can also provide a real time communication session in which the user interacts with a service representative or bot to discuss a loan to purchase the object. Implementations also provide points to the user for taking out a loan to purchase a product, such points redeemable for discounts on future purchases. Point data for the user can be stored on a distributed ledger network.