Credit risk is the most significant risk by impact for any bank and financial institution.
Accurate credit risk assessment affects an organisation's balance sheet and income …

This comprehensive review provides an in-depth analysis of graph theory, various graph
types, and the role of graph visualization in scientific studies. Graphs serve as powerful tools …

External stakeholders require accurate and explainable financial distress prediction (FDP)
models. Complex machine learning algorithms offer high accuracy, but most of them lack …

The strong volatility and randomness of wind power impact the grid and reduce the voltage
quality of the grid when wind power is connected to the grid in large scale. The power sector …

In order to predict wind power quickly and accurately and reduce the negative impact of
wind power instability on the grid, this study proposes an ultra-short-term wind power …

The popularity of the online peer-to-peer (P2P) lending platform in the financial supply chain
(FSC) has grown tremendously in the past few years. However, it is pretty challenging to …

Recently, ensemble-based machine learning models have been widely used and have
demonstrated their efficiency in bankruptcy prediction. However, these algorithms are black …

Accurate assessment of financial distress of SMEs is critical as it has strong implications for
various stakeholders to understand the firm's financial health. Recent studies start to …

Accurate credit risk prediction effectively supports decision makings and risk prevention in
quantitative management. The general paradigm of previous works usually conducts …

Purpose The data economy mainly relies on the surveillance capitalism business model,
enabling companies to monetize their data. The surveillance allows for transforming private …