Abstract Large Language Models (LLMs) trained on large data sets came into prominence in
2018 after Google introduced BERT. Subsequently, different LLMs such as GPT models from …

This study aims to provide a comprehensive overview of risk management research
developments in the energy sector by using bibliometric analysis techniques. We apply the …

To enable more proactive management of the underlying sources of operational risks in
financial institutions, this pre-registered study seeks to improve traditional qualitative …

Nowadays the collection of operational risk data worldwide highly relies on human labor,
leading to slow updates, data inconsistency, and limited quantity. There remains a …

This study investigates the adoption of data analytics in Australian university libraries from
the UTAUT2 perspective, focusing on the factors that influence library professionals' …

The inherent complexity in International Construction Projects (ICPs) brings forth the intricate
interactions between risks, invalidating the risk analysis under the conventional perception …

Higher education institutions (HEIs) in both developed and developing countries are
confronted with increasing pressure to enhance their effectiveness and efficiency while …

The objective of this study is to investigate methodologies concerning enterprise financial
sharing and risk identification to mitigate concerns associated with the sharing and …

Operational risk assessment has received considerable attention in bank risk management.
However, current assessment methods are primarily designed to assess the risk profile of …

Technology is rooting the fintech companies at an unprecedented rate raising the rate of risk
prevailing in this domain. The application of Data Analytics in the fintech industry …