If the comprehensive score is not enough, you can go to the bank to apply for a loan, or you can apply for several online loans, but the pass rate is very low, so it is not recommended for everyone to try. Borrowing users must know the reasons for insufficient comprehensive scores and solve the problems before they can apply for a loan. Generally, the reasons for insufficient comprehensive score are too many personal credit inquiries, too much debt beyond the borrower's repayment ability, bad credit record and untrue personal information. It is recommended that you find your own reasons and improve them before applying. loan, otherwise the overall score will only get worse. After improvement, you can learn about the following formal platforms with lower requirements.

1. Personal comprehensive credit score refers to the use of scientific and rigorous analytical methods to comprehensively examine the internal and external subjective and objective environments that affect individuals and their families, and to fulfill various economic commitments. Ability to make comprehensive judgments and assessments. For different applications, credit scores are divided into risk scores, income scores, responsiveness scores, customer churn (loyalty) scores, collection scores, credit card issuance review scores, mortgage loan issuance review scores, credit limit review scores, etc.

2. Comprehensive credit risk score - Pengyuan 800. At the end of April 2005, the personal comprehensive credit risk score - "Pengyuan 800" independently developed by Pengyuan Credit Information Co., Ltd. was officially approved by credit institutions. Provide credit score inquiry services to individuals. "Pengyuan 800" conducts statistical analysis on personal credit information by establishing a mathematical model to predict the possibility of default risk in the future, and uses a score to comprehensively reflect the personal credit status. This credit scoring system has six levels, ranging from 320 to 800, with each 80-point level quantifying the personal credit status in detail. Each score corresponds to a probability of default. The higher the score, the lower the risk of default. Illustration of scores corresponding to levels and default probability: lowest score 320 400 480 560 640 720 800 highest score F E D C B A .

3. The scoring model uses more than 40 variables related to personal credit, which can be summarized into four categories of variables: personal basic information, bank credit information, personal payment information, and personal capital status. Among them, Bank credit information has the largest weight, close to 50, and the other three types of variables have roughly the same weight. Currently, customers with bank credit records in the credit information system database account for only 25% of the total population. Since bank credit information is the most important variable affecting personal credit status, for customers without bank credit records, the model selects other bank credit-related information. variables are replaced. In the future, as the data gradually improves, we will add more variables to the model to continuously improve the accuracy, precision and universality of the model.