Credit Risk

Credit risk assessment aims to predict the likelihood of borrowers defaulting on loans, informing lending decisions and mitigating financial losses. Current research heavily emphasizes machine learning, employing diverse architectures like graph neural networks (to capture borrower relationships), tree-boosting models (for handling non-linearities and spatio-temporal effects), and transformers (for analyzing textual data), often enhanced by techniques like attention mechanisms and feature engineering. These advancements improve prediction accuracy and offer insights into risk factors, impacting both financial institutions' profitability and the development of more robust risk management strategies.

Papers

October 14, 2024

Hamiltonian Neural Networks for Robust Out-of-Time Credit Scoring
Javier Marín
Credit Scoring Hamiltonian Neural Network Credit Risk Hamiltonian Formulation Credit Risk Model

October 5, 2024

October 3, 2024

A Spatio-Temporal Machine Learning Model for Mortgage Credit Risk: Default Probabilities and Loan Portfolios
Pascal Kündig, Fabio Sigrist
Gaussian Process Spatio Temporal Learning Credit Risk Default Prediction Frailty Care Enterprise Risk

September 23, 2024

Unveiling the Potential of Graph Neural Networks in SME Credit Risk Assessment
Bingyao Liu, Iris Li, Jianhua Yao, Yuan Chen, Guanming Huang, Jiajing Wang
Graph Neural Network Full Potential Risk Prediction Credit Risk

August 27, 2024

Evaluating Credit VIX (CDS IV) Prediction Methods with Incremental Batch Learning
Robert Taylor
Class Incremental Learning Risk Prediction Prediction Method Credit Risk Derivative Process Volatility Index

August 7, 2024

Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENN
Chang Yu, Yixin Jin, Qianwen Xing, Ye Zhang, Shaobo Guo, Shuchen Meng
Machine Learning Model High Dimensional Deep Model Risk Prediction XGBoost Model Credit Risk LightGBM Model SMOTE Integrated

July 16, 2024

Graph Dimension Attention Networks for Enterprise Credit Assessment
Shaopeng Wei, Beni Egressy, Xingyan Chen, Yu Zhao, Fuzhen Zhuang, Roger Wattenhofer, Gang Kou
Graph Attention Network Credit Risk Contagion Effect Financial Network

May 17, 2024

Research on Credit Risk Early Warning Model of Commercial Banks Based on Neural Network Algorithm
Yu Cheng, Qin Yang, Liyang Wang, Ao Xiang, Jingyu Zhang
Back Propagation DH Research Neural Network Model Credit Risk Neural Network Algorithm Default Prediction Financial Risk

April 28, 2024

Innovative Application of Artificial Intelligence Technology in Bank Credit Risk Management
Shuochen Bi, Wenqing Bao
Artificial Intelligence Technology Credit Risk Novel Application Credit Decision

March 11, 2024

Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning
Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou
Graph Neural Network Curriculum Learning Credit Risk Default Prediction Motif Based Graph

February 1, 2024

Attention-based Dynamic Multilayer Graph Neural Networks for Loan Default Prediction
Sahab Zandi, Kamesh Korangi, María Óskarsdóttir, Christophe Mues, Cristián Bravo
Recurrent Neural Network Risk Prediction Credit Scoring Credit Risk Default Prediction

January 29, 2024

Credit Risk Meets Large Language Models: Building a Risk Indicator from Loan Descriptions in P2P Lending
Mario Sanz-Guerrero, Javier Arroyo
Large Language Model Risk Prediction Credit Risk

January 14, 2024

The Effects of Data Imbalance Under a Federated Learning Approach for Credit Risk Forecasting
Shuyao Zhang, Jordan Tay, Pedro Baiz
Mixed Effect Risk Prediction Data Imbalance Imbalanced Datasets Credit Risk Federated Learning Approach

November 17, 2023

Adaptive Modelling Approach for Row-Type Dependent Predictive Analysis (RTDPA): A Framework for Designing Machine Learning Models for Credit Risk Analysis in Banking Sector
Minati Rath, Hema Date
Machine Learning Model Predictive Model Prediction Method Credit Risk Adaptive Model

August 17, 2023

Efficient Commercial Bank Customer Credit Risk Assessment Based on LightGBM and Feature Engineering
Yanjie Sun, Zhike Gong, Quan Shi, Lin Chen
Feature Engineering Credit Risk LightGBM Model Multiple Classifier Customer Behavior

May 8, 2023

UQ for Credit Risk Management: A deep evidence regression approach
Ashish Dhiman
Deep Learning Credit Risk Uncertainty Aware Deep Learning

December 31, 2022

Assessment of creditworthiness models privacy-preserving training with synthetic data
Ricardo Muñoz-Cancino, Cristián Bravo, Sebastián A. Ríos, Manuel Graña
Training Data Synthetic Data Direct Assessment Credit Risk Credit Scoring Model

September 21, 2022

Interpretable Selective Learning in Credit Risk
Dangxing Chen, Weicheng Ye, Jiahui Ye
Inherent Interpretability Logistic Regression Credit Risk Predictive Power

August 28, 2022

Machine Learning Models Evaluation and Feature Importance Analysis on NPL Dataset
Rufael Fekadu, Anteneh Getachew, Yishak Tadele, Nuredin Ali, Israel Goytom
Machine Learning Decision Tree Random Forest Feature Importance Credit Risk Consumer Credit

Credit Risk

Papers

Hamiltonian Neural Networks for Robust Out-of-Time Credit Scoring

Application of AI in Credit Risk Scoring for Small Business Loans: A case study on how AI-based random forest model improves a Delphi model outcome in the case of Azerbaijani SMEs

Applying Hybrid Graph Neural Networks to Strengthen Credit Risk Analysis

A Spatio-Temporal Machine Learning Model for Mortgage Credit Risk: Default Probabilities and Loan Portfolios

Unveiling the Potential of Graph Neural Networks in SME Credit Risk Assessment

Evaluating Credit VIX (CDS IV) Prediction Methods with Incremental Batch Learning

Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENN

Graph Dimension Attention Networks for Enterprise Credit Assessment

Research on Credit Risk Early Warning Model of Commercial Banks Based on Neural Network Algorithm

Innovative Application of Artificial Intelligence Technology in Bank Credit Risk Management

Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning

Attention-based Dynamic Multilayer Graph Neural Networks for Loan Default Prediction

Credit Risk Meets Large Language Models: Building a Risk Indicator from Loan Descriptions in P2P Lending

The Effects of Data Imbalance Under a Federated Learning Approach for Credit Risk Forecasting

Adaptive Modelling Approach for Row-Type Dependent Predictive Analysis (RTDPA): A Framework for Designing Machine Learning Models for Credit Risk Analysis in Banking Sector

Efficient Commercial Bank Customer Credit Risk Assessment Based on LightGBM and Feature Engineering

UQ for Credit Risk Management: A deep evidence regression approach

Assessment of creditworthiness models privacy-preserving training with synthetic data

Interpretable Selective Learning in Credit Risk

Machine Learning Models Evaluation and Feature Importance Analysis on NPL Dataset