Automated Capital Origination Using Point-of-Sale Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Small-to-medium business owners in the hospitality industry face challenges in obtaining capital due to the time-consuming and resource-intensive conventional loan application processes, which often require extensive financial documentation and do not account for industry-specific or seasonal fluctuations in revenue.
Innovation Solution
A system for automated capital origination that uses historical point-of-sale data to generate capital product offers, predicting future revenues and determining interest rates and maximum loan amounts based on probability of default, allowing for dynamic pricing and automatic payment recovery without the need for conventional documentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional loan application processes are used, then capital can be obtained with traditional financial documentation, but the process becomes time-consuming and resource-intensive
Solution Approach 1:
The patent extracts the core underwriting function from the conventional documentation-heavy process. Instead of requiring extensive financial documents, the system uses point-of-sale data as the primary underwriting criterion, eliminating unnecessary documentation steps while maintaining reliable capital origination decisions
Solution Approach 2:
The patent introduces point-of-sale data as an intermediary that bridges the gap between borrower credibility and lender decision-making. This data serves as a reliable proxy for business performance, replacing traditional financial documentation and enabling faster underwriting without sacrificing reliability
2Measurement precision
If extensive financial documentation is required, then traditional underwriting metrics can be calculated, but the burden of documentation increases significantly
Solution Approach 1:
The patent extracts the essential underwriting information from complex financial documentation and consolidates it into point-of-sale data. This single data source provides sufficient information for credit assessment, eliminating the need for balance sheets, income statements, and other extensive documents
Solution Approach 2:
The patent makes point-of-sale data a universal underwriting criterion that serves multiple functions simultaneously: it provides revenue verification, business performance trends, seasonal patterns, and creditworthiness indicators, replacing multiple separate documentation requirements
3Adaptability or versatility
If one-size-fits-all underwriting is applied, then conventional metrics can be used across all industries, but industry-specific and seasonal fluctuations are not accounted for
Solution Approach 1:
The patent applies local quality by tailoring underwriting analysis to each business's specific point-of-sale data patterns. Instead of uniform industry thresholds, the system evaluates each business against its own historical performance, seasonal trends, and operational characteristics, enabling reliable capital pricing that adapts to local business conditions
4Quantity of substance
If SMB owners spend time on loan applications, then capital can be obtained, but hands-on management time decreases and profits are reduced
Solution Approach 1:
The patent enables self-service capital origination where the system automatically evaluates businesses using their existing point-of-sale data. The automated underwriting process requires minimal owner involvement, allowing them to obtain capital without sacrificing hands-on management time, thus maintaining business productivity while securing necessary funding
Data Source
AI summary
A system for automated origination of capital includes a rate processor, a revenue forecaster, and an offer processor. The rate processor generates prices for capital product offers to subscribers of a point-of-sale (POS) subscription service, where the prices are generated by employing probability of default (PD) values that are derived from historical POS data corresponding to each of the subscribers. The revenue forecaster employs the historical POS data to predict future POS data for establishments corresponding to the each of the subscribers and employs the future POS data to generate predicted total revenues corresponding to the each of the subscribers over a payback period. The offer processor generates and transmits the capital product offers corresponding to the each of the subscribers, where the capital product offers comprise the payback period, the prices, and maximum dollar amounts that are a percentage of the predicted total revenues.