The role of data analytics within operational risk management: A systematic review from the financial services and energy sectors

N Cornwell, C Bilson, A Gepp, S Stern… - Journal of the …, 2023 - Taylor & Francis
Operational risks are increasingly prevalent and complex to manage in organisations,
culminating in substantial financial and non-financial costs. Given the inefficiencies and …

Interpretable Machine Learning for Undeclared Work Prediction

E Alogogianni, M Virvou - 2023 14th International Conference …, 2023 - ieeexplore.ieee.org
Machine learning models have vastly proved their contribution to decision-making in many
aspects of daily life. Yet, their acceptance is confined, especially in public authorities, due to …

Prediction of Safety Performance by Using Machine Learning Algorithms: Evidence from Indian Construction Project Sites

SVS Rajaprasad, R Mukkamala - International Journal of …, 2023 - publisher.uthm.edu.my
The construction industry in India happens to be the second most contributor to its gross
domestic product (GDP) but high rates of accidents and fatalities have tarnished the image …

[PDF][PDF] Data-Driven Operational Risk Management: An improved understanding of the effect of causal factors

N Cornwell - 2023 - research.bond.edu.au
The internal and external operating environments of organisations globally are evolving and
becoming more complex, interconnected and volatile. This is leading to greater operational …

Real-Time Analytics and Visualisation of Construction Safety Data Generated Through a Cloud-Based Application

M Flynn, SR RazaviAlavi, N Gerami Seresht - 2021 - nrl.northumbria.ac.uk
Within the construction industry, Health & Safety (H&S) is one of the leading concerns.
Although a significant amount of H&S data is collected, they are not being used effectively …