Glossary of Terms

Next Generation Data Quality

Definition

The use of advanced AI, machine learning, and real-time data validation to ensure that borrower information is accurate, complete, and actionable throughout the loan application process. High-quality data is critical for making fast, accurate lending decisions while reducing risk.

Why is it important to SBA Lending

SBA loans require extensive borrower data, including financial statements, tax records, and business credentials. Poor data quality leads to:
-Loan application rejections due to missing or incorrect information.
-Higher processing costs from manual data verification.
-Increased compliance risks due to inaccurate reporting.

Lenders who implement Next Generation Data Quality benefit from:
-Reduced errors and fraud risks through automated data validation.
-Faster loan processing times by minimizing manual corrections.
-More accurate risk assessments, leading to better lending decisions.

What role does Parlay Play

Parlay’s Loan Intelligence System (LIS) ensures Next Generation Data Quality by:
-Automatically verifying applicant data against financial, tax, and compliance records.
-Integrating external APIs to enrich borrower profiles with real-time business intelligence.
-Using AI-driven analytics to detect inconsistencies and missing information.

With Next Generation Data Quality, Parlay helps lenders make smarter, faster lending decisions while reducing risk and operational inefficiencies.

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