The National Student Loan Data System (NSLDS) is the national database of information about loans and grants awarded to students under Title IV of the Higher Education Act (HEA) of 1965. NSLDS provides a centralized, integrated view of Title IV loans and grants during their complete life cycle, from aid approval through disbursement, repayment, deferment, delinquency, and closure.

Complete set of loan-level data on the recipients of Paycheck Protection Program loans

HERA Section 1212k requires FHFA to prepare a Public Use Database containing information on their loan purchases at the Census Tract level.

Dataset

This dataset was created by Ross Warren

Contents

Abstract

The CoreLogic Loan-Level Market Analytics (LLMA) for primary mortgages dataset contains detailed loan data, including origination, events, performance, forbearance and inferred modification data.

Methodology

CoreLogic sources the Loan-Level Market Analytics data directly from loan servicers. CoreLogic cleans and augments the contributed records with modeled data. The Data Dictionary indicates which fields are contributed and which are inferred.

The Loan-Level Market Analytics data is aimed at providing lenders, servicers, investors, and advisory firms with the insights they need to make trustworthy assessments and accurate decisions. Stanford Libraries has purchased the Loan-Level Market Analytics data for researchers interested in housing, economics, finance and other topics related to prime and subprime first lien data.

CoreLogic provided the data to Stanford Libraries as pipe-delimited text files, which we have uploaded to Data Farm (Redivis) for preview, extraction and analysis.

For more information about how the data was prepared for Redivis, please see CoreLogic 2024 GitLab.

Usage

Per the End User License Agreement, the LLMA Data cannot be commingled (i.e. merged, mixed or combined) with Tax and Deed Data that Stanford University has licensed from CoreLogic, or other data which includes the same or similar data elements or that can otherwise be used to identify individual persons or loan servicers.

The 2015 major release of CoreLogic Loan-Level Market Analytics (for primary mortgages) was intended to enhance the CoreLogic servicing consortium through data quality improvements and integrated analytics. See **CL_LLMA_ReleaseNotes.pdf **for more information about these changes.

For more information about included variables, please see CL_LLMA_Data_Dictionary.pdf.

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For more information about how the database was set up, please see LLMA_Download_Guide.pdf.

Bulk Data Access

Data access is required to view this section.

Synthesised loan risk database data on Loans to non-financial corporations includes loan amounts, maturities, and interest rates. To be accurate but not identify specific companies, the data was synthesised using specific software.

SBA Coronavirus (COVID-19) Relief Options: Economic Injury Disaster Loan (EIDL) Loans Report

United States WAS: Refinance Loans % of the Total Loan Amounts data was reported at 32.700 % in 20 Jul 2018. This records an increase from the previous number of 31.900 % for 13 Jul 2018. United States WAS: Refinance Loans % of the Total Loan Amounts data is updated weekly, averaging 47.010 % from Jan 1990 (Median) to 20 Jul 2018, with 1490 observations. The data reached an all-time high of 86.500 % in 09 Jan 2009 and a record low of 9.990 % in 10 Mar 1995. United States WAS: Refinance Loans % of the Total Loan Amounts data remains active status in CEIC and is reported by Mortgage Bankers Association. The data is categorized under Global Database’s USA – Table US.KA016: Weekly Applications Survey: Mortgage Loan Applications.

Individual car loan status statistical trend data (Financial Joint Credit Information Center)

Overview This dataset contains 45,000 records of loan applicants, with various attributes related to personal demographics, financial status, and loan details. The dataset can be used for predictive modeling, particularly in credit risk assessment and loan default prediction.

Dataset Content The dataset includes 14 columns representing different factors influencing loan approvals and defaults:

Personal Information

person_age: Age of the applicant (in years). person_gender: Gender of the applicant (male, female). person_education: Educational background (High School, Bachelor, Master, etc.). person_income: Annual income of the applicant (in USD). person_emp_exp: Years of employment experience. person_home_ownership: Type of home ownership (RENT, OWN, MORTGAGE). Loan Details

loan_amnt: Loan amount requested (in USD). loan_intent: Purpose of the loan (PERSONAL, EDUCATION, MEDICAL, etc.). loan_int_rate: Interest rate on the loan (percentage). loan_percent_income: Ratio of loan amount to income. Credit & Loan History

cb_person_cred_hist_length: Length of the applicant's credit history (in years). credit_score: Credit score of the applicant. previous_loan_defaults_on_file: Whether the applicant has previous loan defaults (Yes or No). Target Variable

loan_status: 1 if the loan was repaid successfully, 0 if the applicant defaulted. Use Cases Loan Default Prediction: Build a classification model to predict loan repayment. Credit Risk Analysis: Analyze the relationship between income, credit score, and loan defaults. Feature Engineering: Extract new insights from employment history, home ownership, and loan amounts. Acknowledgments This dataset is synthetic and designed for machine learning and financial risk analysis.

China Loan: Real Estate data was reported at 6,254.639 RMB bn in 2016. This records an increase from the previous number of 6,004.909 RMB bn for 2015. China Loan: Real Estate data is updated yearly, averaging 4,527.510 RMB bn from Dec 2010 (Median) to 2016, with 7 observations. The data reached an all-time high of 6,254.639 RMB bn in 2016 and a record low of 3,355.974 RMB bn in 2010. China Loan: Real Estate data remains active status in CEIC and is reported by The People's Bank of China. The data is categorized under China Premium Database’s Money and Banking – Table CN.KB: Loan: By Industry.

Comprehensive dataset of 54,119 Loan agencies in United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The Department of Energy's Loan Programs-administered by LPO-enable DOE to work with private companies and lenders to mitigate the financing risks associated with clean energy projects, and thereby encourage their development on a broader and much-needed scale. The Loan Programs consist of three separate programs managed by two offices, the Loan Guarantee Program Office (LGP) and the Advanced Technology Vehicles Manufacturing Loan Program Office. LPO originates, guarantees, and monitors loans to support clean energy projects through these programs. The programs are: Section 1703: Under Section 1703 of Title XVII, DOE LGP is authorized to guarantee loans for projects that employ new or significantly improved energy technologies and avoid, reduce or sequester air pollutants or greenhouse gases. Section 1705: Under Section 1705 of Title XVII, added by the American Reinvestment and Recovery Act (ARRA), DOE LGP is authorized to guarantee loans for certain clean energy projects that commenced construction on or before September 30, 2011. The Section 1705 program expired, pursuant to statute, on September 30, 2011 and will actively monitor projects that previously received loan guarantees under the 1705 program. LPO will no longer issue new loan guarantees under the 1705 program. Advanced Technology Vehicles Manufacturing (ATVM): Under Section 136 of the Energy Independence and Security Act of 2007, DOE is authorized to provide direct loans to finance advanced vehicle technologies.

Comprehensive dataset of 48 Loan agencies in Vermont, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 1,509 Loan agencies in New York, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

United States Loan Officer Survey: CSE: Other Banks: % Eased Somewhat data was reported at 0.000 % in Apr 2018. This records a decrease from the previous number of 12.000 % for Jan 2018. United States Loan Officer Survey: CSE: Other Banks: % Eased Somewhat data is updated quarterly, averaging 7.400 % from Jan 2015 (Median) to Apr 2018, with 14 observations. The data reached an all-time high of 14.700 % in Apr 2015 and a record low of 0.000 % in Apr 2018. United States Loan Officer Survey: CSE: Other Banks: % Eased Somewhat data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.KA051: Senior Loan Officer Opinion Survey: Residential Mortgage Loans.

Locations and characteristics of projects that have received USDA Rural Development Community Facilities Loans, Grants, and Guaranteed Loans. Includes latitude and longitude coordinates, facility name and address, NAICS Code, funding type, obligation date and amount, total development cost, borrower name and type, and more

Comprehensive dataset of 1,108 Loan agencies in Virginia, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The zero-rate eco-loans base has been recording data on operations financed by zero-rate eco-loans since 2009. These data, obtained in the context of the distribution of these loans subsidised by the State, are transmitted by the credit institutions which distribute it under an agreement with the State and the SGFGAS (Société de Gestion des Financesments et de la Guarantee de l’Accession Sociale à la propriété). This database lists in particular the year of issue of the eco-loan, the type of eco-loan, its geographical location, the total amount of the work, the duration and the amount of the eco-loan.