Patent Application for Private Credit Asset Data Retrieval and Validation

ChangeBridge: Patent Apps - Business Methods (G06Q)

Detected March 27th, 2026

Summary

The USPTO has published a patent application (US20260087549A1) for a system and method for retrieving and validating data associated with private credit assets. The application details a process involving data collection, validation, and the use of an AI module for continuous training and derivation of asset characteristics.

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What changed

This document is a published patent application from the USPTO detailing a novel system and method for managing private credit asset data. The proposed invention focuses on collecting and validating data related to private credit assets, creating identifiers, comparing datasets, and using an artificial intelligence module for continuous training based on validation findings. Concurrently, the system aims to derive characteristics of the private credit asset from the validated data.

While this is a patent application and not a regulation, it signals potential future technological advancements in the financial sector, particularly in areas involving data management, validation, and AI for private credit assets. Compliance professionals should be aware of such innovations as they may influence future operational practices, data security requirements, and the development of new financial products. No immediate compliance actions are required, but monitoring patent trends in fintech can provide insights into evolving industry standards and potential regulatory considerations.

Source document (simplified)

← USPTO Patent Applications

DATA RETRIEVAL AND VALIDATION FOR ONBOARDING PRIVATE CREDIT ASSETS AND DERIVING PRIVATE CREDIT ASSET CHARACTERISTICS

Application US20260087549A1 Kind: A1 Mar 26, 2026

Inventors

Damien Patton, Christian Gratton, Rish Mehta

Abstract

The present invention extends to methods, systems, and computer program products for data retrieval and validation for onboarding private credit assets and deriving private credit asset characteristics. A first set of data associated with a private credit asset is collected. Identifiers associated with the first set of data are created. A second set of data associated with the private credit asset is collected based on the identifiers. The first set of data set and the second set of data are compared based on the identifiers. The first set of data is validated based on the comparison. An artificial intelligence module is trained as part of a continuous training cycle in view of validation findings. Concurrently with artificial intelligence module training, one or more characteristics of the private credit asset are derived from the first set of data.

CPC Classifications

G06Q 40/04 G06F 16/215 G06F 16/2358 G06F 16/2379 G06F 16/275 G06Q 20/363 G06Q 20/3674 G06Q 20/3829 G06Q 20/389 G06Q 20/401 G06Q 20/42 G06Q 30/0613 G06Q 40/06 H04L 9/50 H04L 67/1097 G06Q 2220/00