Rural micro-credit model design and credit risk assessment via improved LSTM algorithm.

ABSTRACT: Rural microcredit plays an important role in promoting rural economic development and increasing farmers' income. However, traditional credit risk assessment models may have insufficient adaptability in rural areas. This study is based on the improved Long Short Term Memory (LSTM) algorithm using self organizing method, aiming to design an optimized evaluation model for rural microcredit risk. The improved LSTM algorithm can better capture the long-term dependence between the borrower's historical behavior and risk factors with its advantages in sequential data modeling. The experimental results show that the rural microcredit risk assessment model based on the self organizing LSTM algorithm has higher accuracy and stability compared to traditional models, and can effectively control credi

SUBMITTER: Gao X 

PROVIDER: S-EPMC10557499 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature