Data Processing System for Retail Financing Pre-Qualification
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Solution Overview
Problem
The conventional process of selling and financing major assets, such as vehicles, is inefficient and inconvenient for customers due to the need for multiple credit inquiries and the risk of financing rejection, leading to wasted resources and potential deal failures.
Innovation Solution
A data processing system that integrates customer and lender data to pre-qualify customers for financing and rank suitable vehicles based on their affordability, streamlining the search process by filtering out vehicles for which the customer is unlikely to qualify for financing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If customers perform multiple credit inquiries to find suitable financing, then they can compare lending options, but the process becomes time-consuming and inconvenient
Solution Approach 1:
The system performs preliminary qualification assessment before the customer selects a vehicle. By pre-determining the customer's financing eligibility and maximum loan amount based on their credit profile, the system eliminates the need for multiple time-consuming credit inquiries during the vehicle selection process.
Solution Approach 2:
The system introduces a third-party qualification service as an intermediary between the customer and multiple lenders. This intermediary assesses the customer's creditworthiness once and provides a standardized qualification result that can be shared with multiple lenders, replacing the need for customers to conduct multiple separate credit inquiries.
2Loss of time
If dealers pre-qualify customers for a particular loan amount, then financing eligibility is determined early, but the customer may still face deal failures if the qualified loan amount is insufficient
Solution Approach 1:
The system changes the parameter of qualification assessment from a fixed pre-determined amount to a dynamic calculation based on the customer's actual credit profile and the specific vehicle being purchased. By adjusting the qualified loan amount parameter to reflect real-time credit assessment results, the system ensures both early determination and deal reliability.
3Ease of operation
If the qualification process occurs after vehicle selection, then customers can choose vehicles freely, but financing rejection risks cause wasted resources and potential deal failures
Solution Approach 1:
The system performs the qualification action preliminarily before vehicle selection. By determining the customer's maximum qualified loan amount in advance, the system enables customers to search for and select vehicles within their financing capabilities, eliminating wasted resources on vehicles that would result in financing rejection.
Solution Approach 2:
The system provides feedback to the customer about their financing eligibility and maximum qualified loan amount before they begin vehicle selection. This feedback loop allows customers to adjust their search criteria to match their financing capabilities, preventing resource waste on unsuitable vehicle selections.
Data Source
AI summary
A method and system for identifying assets in support of a transaction includes obtaining a set of filter values for a customer from each of a plurality of filtering entities. The filtering entities may provide rules, which may be executed in a distributed manner by remote systems, that generate filter values based on input data, or that generate customized filter rules based on the input data. Filter values are used to filter search results produced by a query of a database of assets. Where customized filter rules are generated, the rules are executed against the characteristics of the assets identified in response to the query in order to produce filter values, and the filter values are then used to filter the search results. The search results can be ranked according to a ranking value generated in advance of filtering in order to rank the assets in order of suitability.