Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk management

J Alvi, I Arif, K Nizam - Heliyon, 2024 - cell.com
This research presents a systematic review of a substantial body of high-quality research
articles on Default Prediction Models published from 2015 to 2024. It is a comprehensive …

What should lenders be more concerned about? Develo** a profit-driven loan default prediction model

L Zhang, J Wang, Z Liu - Expert Systems with Applications, 2023 - Elsevier
Reliable and effective loan default risk prediction can help regulators and lenders effectively
identify risky loan applicants and develop proactive and timely response measures to …

[HTML][HTML] Leveraging asynchronous federated learning to predict customers financial distress

A Imteaj, MH Amini - Intelligent Systems with Applications, 2022 - Elsevier
In recent years, as economic stability is shaking, and the unemployment rate is growing high
due to the COVID-19 effect, assigning credit scoring by predicting consumers' financial …

The neuromarketing concept in artificial neural networks: A case of forecasting and simulation from the advertising industry

RR Ahmed, D Streimikiene, ZA Channar, HA Soomro… - Sustainability, 2022 - mdpi.com
This research aims to examine a neural network (artificial intelligence) as an alternative
model to examine the neuromarketing phenomenon. Neuromarketing is comparatively new …

Credit risk prediction model for listed companies based on CNN-LSTM and Attention mechanism

J Li, C Xu, B Feng, H Zhao - Electronics, 2023 - mdpi.com
The financial market has been develo** rapidly in recent years, and the issue of credit risk
concerning listed companies has become increasingly prominent. Therefore, predicting the …

Credit risk management of property investments through multi-criteria indicators

M Locurcio, F Tajani, P Morano, D Anelli, B Manganelli - Risks, 2021 - mdpi.com
The economic crisis of 2008 has highlighted the ineffectiveness of the banks in their
disbursement of mortgages which caused the spread of Non-Performing Loans (NPLs) with …

Optimizing credit limit adjustments under adversarial goals using reinforcement learning

S Alfonso-Sánchez, J Solano… - European Journal of …, 2024 - Elsevier
Reinforcement learning has been explored for many problems, from video games with
deterministic environments to portfolio and operations management in which scenarios are …

Using deep learning to interpolate the missing data in time-series for credit risks along supply chain

W Zhang, MK Lim, M Yang, X Li, D Ni - Industrial Management & Data …, 2023 - emerald.com
Purpose As the supply chain is a highly integrated infrastructure in modern business, the
risks in supply chain are also becoming highly contagious among the target company. This …

Monitoring corporate credit risk with multiple data sources

D Ni, MK Lim, X Li, Y Qu, M Yang - Industrial Management & Data …, 2023 - emerald.com
Purpose Monitoring corporate credit risk (CCR) has traditionally relied on such indicators as
income, debt and inventory at a company level. These data are usually released on a …

Forecasting Credit Risk of SMEs in Supply Chain Finance Using Bayesian Optimization and XGBoost

C Zhang, X Zhou - Mathematical Problems in Engineering, 2023 - Wiley Online Library
Supply chain finance plays a crucial role as a financing channel for small‐and medium‐
sized enterprises (SMEs). However, issues such as financial problems and credit defaults …