Object loss probability determination method and device, computer equipment and storage medium

Abstract

The invention relates to an object loss probability determination method and device, computer equipment, a storage medium and a computer program product, and relates to the technical field of internet finance. The method comprises the following steps: acquiring each service identifier of a target object; determining whether the target service corresponding to each service identifier expires within a rated period; if each target business expires within the rated time limit, inputting the object information of the target object into a pre-trained first prediction model, and determining a first loss probability of the target object by using the first prediction model; and if the business which does not expire within the rated period exists in the target businesses, inputting the object information of the target object into a pre-trained second prediction model, and determining a second loss probability of the target object by using the second prediction model. By adopting the method, the accuracy of determining the object loss probability can be improved, misjudgment on the object loss condition is avoided, and the effectiveness of object maintenance is improved.

Description

technical field [0001] The present application relates to the technical field of Internet finance, and in particular, to a method, apparatus, computer equipment, storage medium and computer program product for determining the probability of loss of an object. Background technique [0002] At present, small and micro enterprises usually use short-term credit as their main source of debt financing due to their short operating history and few mortgage assets. Different from customers of medium and long-term mortgage loans, small and micro credit customers generally need to adjust their short-term liabilities every year to suit their operating conditions, so they have strong short-term credit liquidity. After a short-term credit expires, a small and micro credit customer can generally choose to sign a new short-term credit at the original financial institution (credit provider) or go to another institution to sign a new short-term credit. Therefore, for credit providers such as...

AI Technical Summary

Problems solved by technology

However, in actual operation, it is not accurate to directly use the prediction model to determine the loss probability for different objects, so it will cause misjudgment of the object loss situation and affect the effectiveness of object maintenance

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