Artificial intelligence is a key technology driving digital transformation across all economic
sectors. The prospects and threats of AI in decision-making have been central to public and …

The main objective of this systematic literature review is to unveil the prevailing trend of
employing cutting-edge models for bankruptcy prediction for a period spanning from 2012 to …

Predicting corporate bankruptcy is one of the fundamental tasks in credit risk assessment. In
particular, since the 2007/2008 financial crisis, it has become a priority for most financial …

We examine whether corporate bankruptcy predictions can be improved by utilizing the
recurrent neural network (RNN) and long short-term memory (LSTM) algorithms, which can …

With the unprecedented increase in data all over the world, financial sector such as
companies and industries try to remain competitive by transforming themselves into data …

Using a and a unique set of Italian non-listed Unlikely to Pay (UTP) positions, that consist in
the phase that precedes the insolvency but where it is still possible for the company to …

We use a fully data-driven approach and information provided by the IMF's financial
soundness indicators to measure the condition of a country's financial system around the …

Financial engineering is constantly changing and encountering new problems. Financial
engineering helps us detect emerging trends and challenges, such as fintech's effect on …

This study analyzes the relationship between the housing and stock markets, focusing on
housing market bubbles. Stock market dynamics generally have a more significant impact …

Forecasts of corporate defaults are used in various fields across the economy. Several
recent studies attempt to forecast corporate bankruptcy using various machine learning …