Machine Learning API for Merchant Financing Eligibility

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Solution Overview

Problem

Conventional financing methods for merchants, such as loans and cash advances, often require lengthy application processes and credit checks, making it difficult for them to obtain capital quickly and conveniently.

Innovation Solution

A payment processing system that evaluates merchants' financial transactions to offer financing options without the need for loan applications or credit checks, allowing third-party financial institutions to calculate financing terms and collect repayments directly from transaction funds, using machine learning techniques to determine eligibility and repayment rates.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If conventional loan application processes are used, then financing can be obtained, but the process is lengthy and requires credit checks

Engineering Contradiction:

Improvetime to obtain financingVSAvoidcomplexity of application process

Core Design Contradiction:

Loss of timeVSEase of operation

Solution Approach 1:

The payment processing system continuously collects and analyzes merchant transaction data in advance, pre-calculating creditworthiness and financing eligibility based on historical performance. This preliminary action eliminates the need for time-consuming applications and credit checks at the time of financing request, as the system has already assessed the merchant's financial health through their transaction patterns

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system automatically evaluates merchant financing eligibility and generates offers without requiring merchant initiation or manual credit applications. The payment processing system self-services the entire underwriting process by analyzing transaction data, determining credit risk, and presenting financing options, thereby eliminating complex application procedures and reducing time to obtain financing

Inventive Principle:

Principle #25Self-service

2Productivity

If transaction data is continuously monitored for financing evaluation, then financing decisions can be made quickly, but data privacy and security concerns increase

Engineering Contradiction:

Improvespeed of financing decisionVSAvoiddata privacy risk

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The system extracts only the specific transaction data elements necessary for financing evaluation (such as transaction volume, frequency, and patterns) while leaving sensitive merchant information (customer data, product details, proprietary business information) separate and protected. This selective extraction enables rapid credit assessment without requiring access to or exposure of sensitive merchant data, thus maintaining productivity while reducing privacy risks

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS11593876B1Machine learning for determining an API communication

Publication Date: 2023.02.28 BLOCK INC

AI summary

In some examples, a payment processing system receives transaction information of transactions performed by a plurality of merchants. The payment processing system may generate, using one or more trained machine learning classifiers and based on transaction information of a current transaction of a first merchant, a request to a plurality of financial systems. Further, the payment processing system may expose an application programming interface (API) to at least one financial system of the plurality of financial systems for electronic communication of financial information at least one of to or from the at least one financial system. Additionally, the payment processing system may generate, using the one or more trained machine learning classifiers and based at least on information obtained from the at least one financial system, via the API, one or more payment actions for the first merchant to perform using the payment processing system.