Method and system for pushing financial products in customized mode
A financial product and financial technology, applied in the computer field, can solve problems such as inability to push, poor user experience, and lack of financial management methods, and achieve the effect of improving recommendation accuracy and user experience.
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Embodiment 1
[0063] This embodiment provides a method for customizing and pushing financial products, which belongs to the field of computer technology and is applicable to financial product recommendation business scenarios.
[0064] A method for customizing and pushing financial products provided in this embodiment includes at least the following steps:
[0065] S1. Classify the financial products in the financial platform according to the dimensions of risk, income and cycle, and obtain the classification results of financial products.
[0066] A financial product can be characterized or classified from multiple dimensions, such as risk, return, and cycle. Specifically, it can be divided into high-risk, medium-risk, low-risk, high-yield, medium-yield, low-yield, long-term, medium-cycle, and short-term. Periodic, current and other types.
[0067] When classifying, the risk level, income level and cycle length of financial products can be judged by setting corresponding algorithms or cla...
Embodiment 2
[0118] In order to implement a method for customizing and pushing financial products in the first embodiment above, this embodiment provides a system for customizing and pushing financial products.
[0119] figure 2 Schematic diagram of the system for pushing financial products for this customization, such as figure 2 As shown, the system 100 includes at least:
[0120] Financial product classification module 1: used to classify financial products in the financial platform according to risk, income and cycle dimensions;
[0121] User information acquisition module 2: used to acquire user information of financial platform users;
[0122] Labeling module 3: used to label users through pre-trained classification models based on user information;
[0123] Recommendation module 4: It is used to recommend corresponding products to users through the pre-built financial product recommendation model according to the tagging results;
[0124] Among them, user information includes at...
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