Before you start a project, it is beneficial to assess your client’s financial situation. Experian Connect will let you view the credit report and score of your clients, at no charge, when purchased by your clients. After your client grants you access to their report and score, you can be sure you are seeing their information directly from the credit bureau and not from a scanned copy or print out.
Once you create your account on Experian Connect and you have completed authentication, you can start inviting your potential clients as connections. After they complete authentication and accept your invitation, they will be able to:
You will be able to quickly view your potential client's credit report and score. This may eliminate manual paperwork and save you time – you may be able to make smart decisions faster.
A credit report is a snapshot of your client's experience with credit-related accounts. Aside from some basic personal information, like their name and address to help identify their report, there are three main types of information on their credit report:
A credit score is a number based on the information in your client's credit report. It is similar to a grade you would have received in school, but instead of right and wrong answers, their credit score is based on positive and negative credit history. Paying bills on time and using credit responsibly builds a positive history while paying bills late and being irresponsible with credit builds a negative history.
There are many different ways to calculate a credit score. Experian Connect uses the VantageScore® calculation with the Experian credit report. VantageScore was developed by the three national credit reporting companies — Experian, TransUnion and Equifax. Unlike other scoring systems, it is the most consistent score using only one model with one set of scoring calculations, resulting in scores that are more uniform and consistent.
Developers of credit scoring models review a selection of consumers — often more than one million. The historical credit profiles of these consumers are examined to identify common variables. The developers then build statistical models by selecting the credit variables most predictive of future behavior and assigning appropriate weights to each variable.