LoanScorecard, the leading provider of non-agency automated underwriting systems (AUS), today announced that it has partnered with.
Automated underwriting is a technology-driven underwriting process that provides a computer generated loan decision, and are used to improve the processing time for all types of loans.
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The overwhelming majority of lenders have converted to using the Automated Underwriting System. These programs look at mortgage delinquency risks and credit factors. After the loan application is entered into the system it is quickly combined with a credit report to determine if the applicant is eligible for an approval or not. The Automated Underwriting System benefits both the lender and borrower by cutting down on waiting time.
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Cook: Technically speaking, an AUS is a computer system that analyzes borrower, loan and credit report data and determines whether a borrower qualifies for a loan program based on underwriting guidelines expressed as rules. Therefore, an AUS must have the capability to properly read the input data and apply it to rules that are configured in the AUS such that an automated decision can be made with a high degree of specificity and accuracy.
When you apply for a mortgage loan, your application may go through a automated underwriting system (AUS) for initial pre-approval. Depending on the results, you may need to work with a human underwriter as well before you close on your loan. Find out more about how automated and manual loan approval processes work.
These Automated Underwriting Systems (AUS) make it easy for lenders to process numerous loans while ensuring the loans meet guidelines for investors and regulators. For example, FNMA and FHA loans (among others) require that mortgages fit a particular profile, and most people fit clearly in or outside of the box.
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IRVINE, Calif., June 26, 2019 (GLOBE NEWSWIRE) — LoanScorecard, the leading provider of non-agency automated underwriting systems.
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Automated mortgage underwriting is the process by which lenders evaluate mortgage loan applications using predictive models, artificial intelligence, and machine learning. It provides lenders with a comprehensive risk vs. reward analysis of the borrower. Applications are either approved or denied based on a thorough evaluation of the property and the borrower’s ability to repay the loan.