Income measuring and calculating method applied to LifeCycle

Abstract

The invention belongs to the technical field of measurement and calculation, and particularly relates to a revenue prediction method applied to a borrowing evidence LifeCycle, and the method comprises the steps: calculating the annual daily average balance of a newly added borrowing evidence in each month after the borrowing evidence is put in each month; calculating a weighted average holding day number, establishing a borrowing holding day number variation trend chart based on the weighted average holding day number, and obtaining a convergence point based on the variation trend chart; calculating the average value of the weighted average holding days of the borrowed data put in each month at the convergence point and the weighted average holding days of the annual and daily average balance of the borrowed data LifeCycle; calculating an estimated interest income based on the number of annual and daily average balance weighted average holding days of the borrowed LifeCycle; after the method provided by the invention is adopted, the method is not influenced by a business mode, and the interest income prediction accuracy can reach 95% or above in the estimated income of the credit field of first interest and then local or borrowing and returning at any time; the timeliness in long-term borrowing income calculation is obviously improved, the accuracy is high, and the application range is wide.

Description

technical field [0001] The invention belongs to the technical field of measurement and calculation, and in particular relates to a revenue prediction method applied to IOU LifeCycle. Background technique [0002] IOU revenue estimation is often used in business marketing activities, channel benefit evaluation, KPI measurement and other fields. Accurately estimating benefits is critical to making sound operational decisions. In business operation, the traditional estimate of IOU LifeCycle income is calculated using the IPMT calculation method. This algorithm assumes that the business is a business model in which the principal is repaid on schedule. In actual business, in order to improve the user experience, the model of borrowing and repaying is often used, allowing customers to repay in advance. Under this model, IPMT is no longer directly applicable to income estimation. Generally, IOUs with natural maturity are used as samples to observe the actual loan and repayment si...

AI Technical Summary

Problems solved by technology

On the one hand, this method has obvious hysteresis, and on the other hand, the accuracy of short-term prediction is low; secondly, IPMT lacks the prediction method of the model of interest first, and the accuracy of this algorithm will be further reduced if it is directly applied