Research On A Bank Customer Financial Product Recommendation Model

The advent of the Big Data era brought with it a new surge of speed,spurred on by science and technology.The Internet’s emergence has caused a shift in product forms and transaction methods within the financial sector,leaving traditional marketing techniques unable to keep up with the rapidity of business and the sheer volume of data.Therefore,it has become the current goal of various financial institutions to integrate artificial intelligence algorithm to recommend personalized financial products to customers.A bank’s financial product recommendation model,designed and implemented in accordance with the current situation and demand,has been significantly improved in accuracy compared to the original model,as demonstrated in this paper.This paper makes full use of rich data resources such as customer and product information,trading information and APP behavior information of Bank A,groups full customers according to the trading and position of different customers,and designs corresponding recall and ranking strategies for different customer groups.The hybrid recall strategy designed in this paper integrates popular recall,collaborative filtering,similarity calculation,user behavior and other methods,closely combined with the actual scenario of financial product trading,and recalls products matching customer preferences from multiple dimensions.In the sorting stage,the integrated learning model is selected to further predict and score the recalled financial products,and the top 10 products with the corresponding prediction probability of each customer are selected as the recommendation results,so as to realize the personalized recommendation for each customer.Finally,by means of evaluation index analysis,backtest case analysis and feature importance analysis,comprehensive evaluation and analysis are carried out on the customer financial product recommendation model in this paper.The model’s efficacy is remarkable,particularly in comparison to the original recommendation model employed by Bank A.Its clear benefits are evident,satisfying Bank A’s requirements for financial product recommendation and resolving their current predicaments.