基于BP神经网络和线性规划模型的银行贷款策略  

Bank Loan Strategy Based on BP Neural Network and Linear Programming Model

作　　者：于世鑫 姚泽佳 王浩东 李栋林 YU Shi-xin;YAO Ze-jia;WANG Hao-dong;LI Dong-lin(Hebei Agricultural University,Baoding 071000,China)

机构地区：[1]河北农业大学,河北保定071000

出　　处：《中小企业管理与科技》2021年第16期132-133,共2页Management & Technology of SME

摘　　要：针对中小企业规模相对较小、缺少抵押资产的现状,银行通常依据信贷风险对实力强和供求关系稳定的企业提供贷款,论文通过建立BP神经网络模型和线性规划模型,确定银行信贷的最优策略。首先,对搜集到的数据进行预处理,得到各企业6个指标的综合数据。其次,以供销链复杂度、企业规模、还款能力、负数发票、企业活力5个指标为输入,以信誉评级为输出建立BP神经网络模型。最后,以银行收益期望为目标建立优化模型,从中确定最优的贷款分配策略,使得银行获得最大收益。In view of the relatively small scale of small and medium-sized enterprises and the lack of mortgage assets,banks usually provide loans to enterprises with strong strength and stable supply and demand based on credit risk.This paper establishes BP neural network model and linear programming model to determine the optimal strategy of bank credit.First of all,preprocessing the collected data to get the comprehensive data of six indicators of each enterprise.Secondly,the BP neural network model is established with five indexes of supply and marketing chain complexity,enterprise scale,repayment ability,negative invoice and enterprise vitality as input and credit rating as output.Finally,an optimization model is established with the bank's income expectation as the goal,from which the optimal loan allocation strategy is determined to maximize the bank's income.

关 键 词：银行信贷风险 BP神经网络 线性规划模型 

分 类 号：F830.42[经济管理—金融学] F832.4