scholarly journals Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis

2020 ◽  
Vol 10 (9) ◽  
pp. 3145 ◽  
Author(s):  
Victor Chang ◽  
Raul Valverde ◽  
Muthu Ramachandran ◽  
Chung-Sheng Li

Financialization has contributed to economic growth but has caused scandals, misselling, rogue trading, tax evasion, and market speculation. To a certain extent, it has also created problems in social and economic instability. It is an important aspect of Enterprise Security, Privacy, and Risk (ESPR), particularly in risk research and analysis. In order to minimize the damaging impacts caused by the lack of regulatory compliance, governance, ethical responsibilities, and trust, we propose a Business Integrity Modeling and Analysis (BIMA) framework to unify business integrity with performance using big data predictive analytics and business intelligence. Comprehensive services include modeling risk and asset prices, and consequently, aligning them with business strategies, making our services, according to market trend analysis, both transparent and fair. The BIMA framework uses Monte Carlo simulation, the Black–Scholes–Merton model, and the Heston model for performing financial, operational, and liquidity risk analysis and present outputs in the form of analytics and visualization. Our results and analysis demonstrate supplier bankruptcy modeling, risk pricing, high-frequency pricing simulations, London Interbank Offered Rate (LIBOR) rate simulation, and speculation detection results to provide a variety of critical risk analysis. Our approaches to tackle problems caused by financial services and the operational risk clearly demonstrate that the BIMA framework, as the outputs of our data analytics research, can effectively combine integrity and risk analysis together with overall business performance and can contribute to operational risk research.

2018 ◽  
Vol 169 ◽  
pp. 485-502 ◽  
Author(s):  
Bushra Khan ◽  
Faisal Khan ◽  
Brian Veitch ◽  
Ming Yang

2014 ◽  
Vol 23 (01) ◽  
pp. 27-35 ◽  
Author(s):  
S. de Lusignan ◽  
S-T. Liaw ◽  
C. Kuziemsky ◽  
F. Mold ◽  
P. Krause ◽  
...  

Summary Background: Generally benefits and risks of vaccines can be determined from studies carried out as part of regulatory compliance, followed by surveillance of routine data; however there are some rarer and more long term events that require new methods. Big data generated by increasingly affordable personalised computing, and from pervasive computing devices is rapidly growing and low cost, high volume, cloud computing makes the processing of these data inexpensive. Objective: To describe how big data and related analytical methods might be applied to assess the benefits and risks of vaccines. Method: We reviewed the literature on the use of big data to improve health, applied to generic vaccine use cases, that illustrate benefits and risks of vaccination. We defined a use case as the interaction between a user and an information system to achieve a goal. We used flu vaccination and pre-school childhood immunisation as exemplars. Results: We reviewed three big data use cases relevant to assessing vaccine benefits and risks: (i) Big data processing using crowd-sourcing, distributed big data processing, and predictive analytics, (ii) Data integration from heterogeneous big data sources, e.g. the increasing range of devices in the “internet of things”, and (iii) Real-time monitoring for the direct monitoring of epidemics as well as vaccine effects via social media and other data sources. Conclusions: Big data raises new ethical dilemmas, though its analysis methods can bring complementary real-time capabilities for monitoring epidemics and assessing vaccine benefit-risk balance.


2017 ◽  
Vol 16 ◽  
pp. 43-53 ◽  
Author(s):  
Chengyuan Li ◽  
Mingjun Jiang ◽  
Haiming Ge ◽  
Zhen Li ◽  
Dongkun Luo

2018 ◽  
Vol 17 (2) ◽  
pp. 265-290 ◽  
Author(s):  
PANAGIOTIS DELIMATSIS ◽  
BERNARD HOEKMAN

AbstractCan a WTO Member discriminate against foreign suppliers of services located in jurisdictions that refuse to share information with a government to permit it to determine if its nationals engage in tax evasion? Does it matter if the Member uses standards developed by an international body as the criterion for deciding whether to impose measures? In Argentina–Financial Services, the WTO Appellate Body held that services from jurisdictions that share financial tax information may be different from services provided by jurisdictions that do not cooperate in supplying such information. It overruled a Panel finding that measures to increase taxes on financial transactions with non-cooperative jurisdictions were discriminatory. We argue that the AB reached the right conclusion on the basis of the wrong arguments; that it missed an important opportunity to clarify what WTO Members are permitted to do to enforce their domestic regulatory regimes; and increased the scope for confusion and future litigation by considering that the likeness of services and service suppliers may be a function of prevailing domestic regulatory regimes.


2005 ◽  
Author(s):  
Ana Fernández Laviada ◽  
Francisco J. Martinez Garcia ◽  
Francisco M. Somohano

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