Financial Distress

Financial distress, encompassing bankruptcy prediction for corporations and municipalities, is a critical area of research aiming to improve early detection and mitigation strategies. Current research heavily utilizes machine learning, particularly gradient boosted trees and other advanced algorithms like those offered by automated machine learning platforms, to analyze diverse datasets including financial statements, governance data, and market information. Accurate prediction models are crucial for informed financial decision-making, resource allocation, and ultimately, the stability of economic systems. The incorporation of domain expertise, such as from accounting judiciary experts, is also shown to enhance model accuracy and applicability.

Papers

July 7, 2023

Incentive Allocation in Vertical Federated Learning Based on Bankruptcy Problem
Afsana Khan, Marijn ten Thij, Frank Thuijsman, Anna Wilbik
Machine Learning Model Vertical Federated Learning Private Data Game Theory Passive Party Incentive Allocation Financial Distress

February 23, 2023

Financial Distress Prediction For Small And Medium Enterprises Using Machine Learning Techniques
Yuan Gao, Biao Jiang, Jietong Zhou
Machine Learning Prediction Model Financial Data Small and Medium Sized Enterprise FCM Deep Neural Network Financial Distress

February 11, 2023

Predicting municipalities in financial distress: a machine learning approach enhanced by domain expertise
Dario Piermarini, Antonio M. Sudoso, Veronica Piccialli
Machine Learning Model Machine Learning Approach Domain Expertise Urban Prediction Financial Distress

December 22, 2022

Benchmarking Machine Learning Models to Predict Corporate Bankruptcy
Emmanuel Alanis, Sudheer Chava, Agam Shah
Machine Learning Random Forest Credit Scoring Machine Learning Benchmark Financial Distress

December 7, 2022

Fallen Angel Bonds Investment and Bankruptcy Predictions Using Manual Models and Automated Machine Learning
Harrison Mateika, Juannan Jia, Linda Lillard, Noah Cronbaugh, Will Shin
Machine Learning Full Model Predictive Performance Optimal Learning Bankruptcy Prediction Financial Distress

September 10, 2022

CoreDeep: Improving Crack Detection Algorithms Using Width Stochasticity
Ram Krishna Pandey, Akshit Achara
Perceptual Quality Crack Detection Class Variability Financial Distress Robust Width