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A personalized recommendation method based on risk-benefit management on a p2p platform

A technology for recommending methods and platforms, applied in data processing applications, finance, instruments, etc., can solve problems such as inability to achieve, achieve high returns, speed up convergence, and save system resource consumption.

Active Publication Date: 2021-07-16
ANHUI UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing work on risk assessment usually aims to achieve stable low returns while reducing risks, but cannot meet the requirement of recommending low-risk high-yield loans to investors

Method used

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  • A personalized recommendation method based on risk-benefit management on a p2p platform
  • A personalized recommendation method based on risk-benefit management on a p2p platform
  • A personalized recommendation method based on risk-benefit management on a p2p platform

Examples

Experimental program
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Embodiment Construction

[0058] In this example, a personalized recommendation method based on risk-return management on the P2P platform transforms the loan recommendation problem in the P2P lending platform into a loan portfolio recommendation problem based on multi-objective optimization, and combines the NSGA-Ⅱ algorithm framework to solve the loan portfolio recommendation problem problem, so as to obtain a different set of optimal loan portfolios for each user in the platform; such as figure 1 As shown, specifically, proceed as follows:

[0059] Step 1. Define the user set including all users in the P2P lending platform as U={u 1 ,u 2 ,...,u n}. Define the loan set including all loans in the platform as V={v 1 ,v 2 ,...,v m}. For any loan v j Both exist with a final state (Defaulted (-1), Canceled (0), Deferred (1), and Repaid (2)). The weighted probability propagation algorithm is obtained by improving the probability propagation algorithm to model and analyze the existing transaction d...

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Abstract

The invention discloses a personalized recommendation method based on risk and return management on a P2P platform. The method converts the loan recommendation problem in the P2P lending platform into a multi-objective optimization problem, and constructs the historical investment records of investors in the P2P platform. Model analysis, problem transformation, population initialization and population evolution are used to solve the loan recommendation problem in the P2P platform. The different loan combinations recommended by the present invention to different users not only conform to the user's interest preferences, but also can obtain good returns under the premise of lower risks, thereby improving the user's trust in the P2P lending platform, and thus making P2P The lending platform can operate and develop better.

Description

technical field [0001] The invention relates to the field of loan recommendation on a P2P platform, in particular to a personalized recommendation method based on risk and return management on a P2P platform. Background technique [0002] P2P lending is an emerging business model that pools small amounts of capital to provide loans to those in financial need. The social impact of P2P lending services is mainly reflected in three aspects, namely, satisfying personal capital needs, developing a personal credit system, and improving the utilization rate of a small amount of funds. In recent years, online P2P lending platforms have developed rapidly. For example, Prosper is one of the largest online lending platforms in the United States, currently has more than 2.2 million members and more than 13 billion in loans. This lending model is a win-win for both borrowers and lenders. The seller (investor) can obtain higher interest income than the bank, while for the buyer (borrow...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q40/02
Inventor 张磊吴鑫鹏
Owner ANHUI UNIVERSITY
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