TRAiNED (20240378666). SYSTEM AND METHODS FOR AUTOMATED LOAN ORIGINATION DATA VALIDATION AND LOAN RISK BIAS PREDICTION simplified abstract

SYSTEM AND METHODS FOR AUTOMATED LOAN ORIGINATION DATA VALIDATION AND LOAN RISK BIAS PREDICTION

Organization Name

TRAiNED

Inventor(s)

Jonathan Freed of Bridgeville PA (US)

David John Paulina, Jr. of McMurray PA (US)

Kyle Scott W. Jenkins of New Kensington PA (US)

George Salvatore Goehring of Coraopolis PA (US)

Nicholas J. Goossen of Moon Township PA (US)

Joseph Arthur Friedman of Pittsburgh PA (US)

Jason Scott Overand of Pittsburgh PA (US)

Christina Soukhamneut of Savannah GA (US)

Janet Louise Wilson of Morton PA (US)

Jennifer Ann Auvinen of Winnemucca NV (US)

SYSTEM AND METHODS FOR AUTOMATED LOAN ORIGINATION DATA VALIDATION AND LOAN RISK BIAS PREDICTION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240378666 titled 'SYSTEM AND METHODS FOR AUTOMATED LOAN ORIGINATION DATA VALIDATION AND LOAN RISK BIAS PREDICTION

The platform described in the abstract is a system that validates loan origination data and provides predictive analysis. It includes a user interface for data upload, a data acquisition engine that uses machine and/or deep learning algorithms to classify and validate data, and an artificial intelligence engine that constructs and maintains models.

• User interface for data upload
• Data acquisition engine using machine and/or deep learning algorithms
• Artificial intelligence engine for model construction
• Integration with lender institution loan origination systems
• Central, secure repository for borrower documentation
• Trained generative AI model for predictive analysis

Potential Applications: - Streamlining loan origination processes - Improving data accuracy and compliance - Enhancing predictive analysis for decision-making

Problems Solved: - Data validation and classification - Compliance enforcement - Predictive analysis for loan applications

Benefits: - Increased efficiency in loan origination - Improved decision-making accuracy - Enhanced data security and compliance

Commercial Applications: Title: "Enhancing Loan Origination Processes with Data Validation and Predictive Analysis" This technology can be used by financial institutions, lending companies, and credit agencies to streamline loan origination processes, improve data accuracy, and enhance predictive analysis for better decision-making. It can lead to increased efficiency, improved risk assessment, and enhanced customer experience in the lending industry.

Prior Art: Researchers in the field of artificial intelligence and machine learning have developed similar platforms for data validation and predictive analysis in various industries. It would be beneficial to explore prior art related to loan origination processes and financial data analysis.

Frequently Updated Research: Stay updated on advancements in machine learning algorithms, deep learning techniques, and artificial intelligence models for data validation and predictive analysis in the financial sector.

Questions about the platform: 1. How does the platform ensure data security and compliance? The platform utilizes a central, secure repository for borrower documentation and leverages compliance enforcement algorithms to ensure data security and regulatory compliance.

2. What are the potential challenges in integrating the platform with lender institution loan origination systems? Integrating the platform with lender systems may require custom APIs and data mapping to ensure seamless data transfer and compatibility.

Original Abstract Submitted

a platform which provides a system and method for loan origination data validation and predictive analysis comprising a user interface which allows platform users to upload data, a data acquisition engine that leverages one or more machine and/or deep learning algorithms to classify, validate, and enforce compliance of the uploaded data, and an artificial intelligence engine that constructs and maintains the models developed from the machine and/or deep learning algorithms. the platform may utilize various bespoke apis to integrate validated data with lender institution loan origination systems when a lender initiates the process. the platform can function as a system of record and central, secure repository for a borrower's documentation and information required to apply for a loan. in some embodiments, the platform utilizes a trained generative ai model to assist platform users and to provide predictive analysis responsive to user submitted queries.