Abstract

Economic development has provided good opportunities for the development of securities companies. Similarly, the development of Internet technology has also brought huge opportunities and challenges to the development of securities companies. Aiming at the current wealth management issues in the era of mobile Internet, this article attempts to develop a personalized recommendation approach on the basis of users’ behavioral data analysis. We analyzed and judged the current situation of mobile Internet wealth management using personalized recommendation systems. On the basis of personalized recommendation, we use the user’s interest tags, personalized recommendation technology, and data mining technology to analyze and summarize customer transaction records. This is done through the use of preservation of customer transaction data. By understanding customers’ investment needs, risk preferences, and other information, we can segment customers and provide them with targeted products and services. As a result of the study, a flexible personalized recommendation framework is designed and validated for mobile Internet wealth management services. The effectiveness of the proposed approach is verified through testing of the developed model.

Highlights

  • Traditional third-party wealth management is a provider of “financial products” and “professional services,” acquiring customers through offline activities, development channels, and telemarketing [1]

  • A personalized recommendation system for mobile Internet wealth management is proposed which is based on the user behavior data analysis

  • Recommendations Based on Personalized Wealth Management. e algorithm is based on the basic idea that similar users have similar interests and hobbies. It is the earliest and most successful recommendation application technology. is section proposes the collaborative filtering recommendation algorithm M-collaborative filtering algorithm (CF) based on the user interest model and uses the real-time user interest model proposed in Section 4 to express the user’s hobbies

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Summary

Introduction

Traditional third-party wealth management is a provider of “financial products” and “professional services,” acquiring customers through offline activities, development channels, and telemarketing [1]. In this way, material resources must be invested offline, and the cost is high. By studying the innovation of the financial industry, that the rapid development of Internet technology has significant impact on the brokerage services [9]. Aiming at the current wealth management issues, this article attempts to develop a personalized recommendation scheme based on user behavior data analysis. A personalized recommendation system for mobile Internet wealth management is proposed which is based on the user behavior data analysis. (iii) On the basis of understanding the customer's investment needs and risk appetite and other information, we segment the customers and provide customized and personalized products

Related Technology Overview
Mobile Internet Wealth Management Based on Personalized Recommendation
Personalized Recommendation Model Test
Conclusion
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