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Article

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

1
School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK
2
John Molson School of Business, Concordia University, Montreal, QC H3G 1M8, Canada
3
School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds LS16 5LF, UK
4
PwC Lab, PwC, San Jose, CA 95110, USA
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(9), 3145; https://doi.org/10.3390/app10093145
Submission received: 28 December 2019 / Revised: 14 April 2020 / Accepted: 15 April 2020 / Published: 30 April 2020

Abstract

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.
Keywords: financialization; Business Integrity Modeling and Analysis (BIMA) framework; Monte Carlo simulations and Black Scholes models; financial cloud analytics; risk management financialization; Business Integrity Modeling and Analysis (BIMA) framework; Monte Carlo simulations and Black Scholes models; financial cloud analytics; risk management

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MDPI and ACS Style

Chang, V.; Valverde, R.; Ramachandran, M.; Li, C.-S. Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis. Appl. Sci. 2020, 10, 3145. https://doi.org/10.3390/app10093145

AMA Style

Chang V, Valverde R, Ramachandran M, Li C-S. Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis. Applied Sciences. 2020; 10(9):3145. https://doi.org/10.3390/app10093145

Chicago/Turabian Style

Chang, Victor, Raul Valverde, Muthu Ramachandran, and Chung-Sheng Li. 2020. "Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis" Applied Sciences 10, no. 9: 3145. https://doi.org/10.3390/app10093145

APA Style

Chang, V., Valverde, R., Ramachandran, M., & Li, C.-S. (2020). Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis. Applied Sciences, 10(9), 3145. https://doi.org/10.3390/app10093145

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