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Computational approaches and data analytics in financial services: A literature review
The level of modeling sophistication in financial services has increased considerably over
the years. Nowadays, the complexity of financial problems and the vast amount of data …
the years. Nowadays, the complexity of financial problems and the vast amount of data …
[HTML][HTML] Modelling supply chain disruption analytics under insufficient data: A decision support system based on Bayesian hierarchical approach
Recent disruptions in global and local supply chains (SCs) due to manmade and natural
disasters have drawn a lot of attention to academics and practitioners. Such disruptions are …
disasters have drawn a lot of attention to academics and practitioners. Such disruptions are …
Deep learning to improve the sustainability of agricultural crops affected by phytosanitary events: A financial-risk approach
Given the challenges in reducing greenhouse gases (GHG), one of the sectors that have
attracted the most attention in the Sustainable Development Agenda 2030 (SDA-2030) is the …
attracted the most attention in the Sustainable Development Agenda 2030 (SDA-2030) is the …
Fuzzy analytic network process with principal component analysis to establish a bank performance model under the assumption of country risk
In recent years, bank-related decision analysis has reflected a relevant research area due to
key factors that affect the operating environment of banks. This study's aim is to develop a …
key factors that affect the operating environment of banks. This study's aim is to develop a …
Fuzzy convolutional deep-learning model to estimate the operational risk capital using multi-source risk events
Operational Risk (OR) is usually caused by losses due to human errors, inadequate or
defective internal processes, system failures or external events that affect an organization …
defective internal processes, system failures or external events that affect an organization …
Identification of Fintech driven operational risk events
F Khalil, HM Alam - Journal of the Research Society of …, 2020 - search.proquest.com
The purpose of this study is to identify the Fintech driven operational risk events as no
historical data is available. For this, the study reviews the literature to list down possible OR …
historical data is available. For this, the study reviews the literature to list down possible OR …
Ambiguous requirements: A semi-automated approach to identify and clarify ambiguity in large-scale projects
In large-scale projects, the client defines a set of product requirements, which the provider is
then expected to deliver within the agreed time, cost and scope. If a client sets ambiguous …
then expected to deliver within the agreed time, cost and scope. If a client sets ambiguous …
[HTML][HTML] Deep Fuzzy Credibility Surfaces for Integrating External Databases in the Estimation of Operational Value at Risk
Operational risk (OR) is usually caused by losses due to human errors, inadequate or
defective internal processes, system failures, or external events that affect an organization …
defective internal processes, system failures, or external events that affect an organization …
A multispectral image classification framework for estimating the operational risk of lethal wilt in oil palm crops
Operational risk is the risk associated with business operations in an organisation. With
respect to agricultural crops, in particular, operational risk is a fundamental concept to …
respect to agricultural crops, in particular, operational risk is a fundamental concept to …
Stochastic logistic fuzzy maps for the construction of integrated multirates scenarios in the financing of infrastructure projects
In general, the development of economic infrastructure systems requires a behavioural
comprehensive analysis of different financial variables or rates to establish its long-term …
comprehensive analysis of different financial variables or rates to establish its long-term …