Big data credit is the use of data analysis and modeling for risk assessment, based on the assessment score, to predict the repayment ability, willingness to repay, and fraud risk of the repayer. In the field of financial risk control, big data refers to the full amount of data and user behavior data.

What is currently used is the data surrounding the customer that is highly relevant to the customer's credit situation, and the data is utilized to implement scientific risk control.

1, big data credit model can make credit evaluation more accurate: big data credit model incorporates massive data into the credit system and analyzes it from multiple angles with multiple credit models.

2, big data credit can incorporate more diversified behavioral data: in the era of big data, every relevant organization is trying to obtain the data information of the actors to the greatest extent possible, so that the data covers a wide range of data to the greatest extent possible, and the data is fresh in real time.

3, big data credit brings a more current judgment standard: another shortcoming of traditional risk control is the lack of effectiveness data input, its risk control model reflects the results of lagging data often. Using the assessment results of lagging data to manage credit risk inherently creates greater structural risk.

Big data reasons for bad credit records

Credit big data black, is the emergence of bad credit records, when there is a bad credit record, can only continue to maintain good credit, the use of 5 years later will not be displayed again. It cannot be deactivated and the information is no longer updated after deactivation.

According to the Regulations on the Administration of the Credit Collection Industry, bad information is displayed for 5 years from the date of termination of the bad behavior or event.

For credit businesses whose accounts are in the normal opening period, the credit center will update them every month. However, the credit business will not have its information updated after the account is canceled or closed.

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