Credit Rating Data: Best Credit Rating Datasets & Database Sources
What is Credit Rating Data?
Credit rating data is data that provides intelligence on the financial capabilities of individuals or companies seeking credit facilities. It includes information on their previous performance when it comes to borrowing money, projected cashflows, and any other information that may give lenders insight on how feasible giving out the credit facility is. Examples of credit rating data include credit scores, credit reports, and credit ratings assigned to individuals or businesses by credit rating agencies.
Best Credit Rating Datasets & APIs
EDI Credit Default Swap (CDS) Data Global Coverage | 2000+ Reference Entities | Bond Credit Rating | Fixed Income Data | 10 years historic data
Opah Labs Consumer Credit Rating Data for Leasing Products | United States | 74M+ Records
Corporate Credit Rating data for Global companies across 230+ countries
Factori Consumer Purchase Data | USA | 200M+ profiles, 100+ Attributes | Behavior Data, Interest Data, Email, Phone, Social Media, Gender, Linkedin
Bank Rating Report for African Financial Institutions
Versium REACH - B2C Consumer Address Enrichment, USA, CCPA Compliant
McGRAW Debt and Consumer Spending DataâReal Time & Aged Debt Leadsâ273MM Records
TagX - Synthetic Bank Statements Data | Savings account / Checking accounts / Business accounts | Global coverage
Factori | US Consumer Graph Data - Acquisition Marketing & Consumer Data Insights | Append 100+ Attributes from 220M+ Consumer Profiles
Bank Rating Report for European Financial Institutions
Monetize data on Datarade Marketplace
Credit Rating Data Use Cases
Credit Rating Data Explained
How is Credit Rating Data collected?
Both businesses and individuals have credit scores, which are statements of their financial positions. Credit rating data providers gather this data, combining it with a scoring algorithm. The final result is what is used as credit rating data. Statements of financial positions can be gathered from company registries, or public records for companies, and for individuals, they can be accessed through bank or book keeping data. Based on the information accrued, a scoring model is created, and it is this model that determines whether to approve a loan and what interest rate to charge, based on the borrowerâs eligibility and financial ability.
What are the attributes of Credit Rating Data?
A typical credit rating dataset exists for the purpose of rating the creditworthiness or eligibility of an individual or business. Therefore, it would typically be comprised of information that describes the financial activities of the borrower. The level of detail depends on what sort of economic activity that the individual or company is involved in. In light of this, there are attributes of a credit rating dataset that are constant across all cases. They are: a history of the business or individualâs payments or expenditures; information on their history with credit (that is, if they have borrowed before, and how it went the last time); previous uses of credit facilities; what type of credit facilities have been requested, and any new credit facilities theyâve used. Individual income and personal wealth also are important to credit rating, so frequently feature in credit rating datasets.
What is Credit Rating Data used for?
Credit rating data plays a prominent role in the credit facilities industry. It helps run operations in this sector smoothly. Credit rating data can be used in credit risk analysis, especially by banks and other lending financial institutions to determine the extent of risk on loaning out to a particular individual or business. Credit rating data is also useful for managing risk in credit, risk assurance, predictive analysis and other financial information related use cases. In the development of expansion strategy, credit rating is also useful information, as it helps to map out policies and means by which expansion can be achieved safely.
How can a user assess the quality of Credit Rating Data?
To assess the quality of credit rating data, then it must be timely to be useful. Check whether itâs up-to-date. Credit rating data must have been verified as accurate data from various sources. It should also pass the test for any errors and omissions. It is also important that you verify the credibility of the data provider to complete the metrics of data quality assessment on a dataset.