@article {Iraqi2021506,
	title = {Data Analytics in Investment Banks},
	journal = {International Journal of Advanced Computer Science and Applications},
	volume = {12},
	number = {5},
	year = {2021},
	note = {cited By 0},
	pages = {506-513},
	abstract = {Capital Markets are one of the most important pillars of worldwide economy. They gather skilled finance and IT professionals as well as economists in order to take the best investment decisions and choose the most suitable funding solutions every time. Data analytics projects in Capital Markets can definitely be very beneficial as all optimizations and innovations would have a financial impact, but can also be very challenging as the field itself has always incorporated a research component, thus finding out what could really be of an added value might be a tricky task. Based on a comprehensive literature review, this paper aims to structure the thoughts around data analytics in investment banks, and puts forward a classification of relevant data analytics use cases. Lastly, it also discusses how transforming to a data-driven enterprise is the real change investment banks should aim to achieve, and discusses some of the challenges that they might encounter when engaging in this transformation process. {\textcopyright} 2021. All Rights Reserved.},
	keywords = {Commerce, Data analytic use case, Data Analytics, Data driven, Data-driven transformation, Financial impacts, Financial markets, Investment bank, Investment decisions, Investments, IT professional, Metadata, Optimisations},
	doi = {10.14569/IJACSA.2021.0120562},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107532071\&doi=10.14569\%2fIJACSA.2021.0120562\&partnerID=40\&md5=7237f6b38c7eedbe1f23bb2968802d60},
	author = {Iraqi, B. and Benhiba, L. and Idrissi, M.A.J.}
}
@article {Chaker20176182,
	title = {The dynamic adaptive sustainability balanced scorecard: A new framework for a sustainability-driven strategy},
	journal = {International Journal of Applied Engineering Research},
	volume = {12},
	number = {16},
	year = {2017},
	note = {cited By 0},
	pages = {6182-6191},
	abstract = {The Sustainability Balanced Scorecard (SBSC) has been widely recognized as a valuable decision aid approach in the management of sustainability. Controversy is nevertheless still prevalent on which SBSC architecture is most suitable for which organizational context. Moreover, the literature unveils some structural flaws in SBSC design methodologies that remain up till now fundamentally based on intuitionist mental models and subjective judgment. Building upon existing critical evaluations and the gaps to be addressed, we propose in this paper a new sustainability decision aid framework based on a novel combination of Multi-Criteria Decision Making methods (MCDM), Fuzzy logic, and System Dynamics modeling. The resulting framework, denoted as the Dynamic Adaptive SBSC (D-ASBSC), offers the advantage of high adaptability, comprehensiveness, and unbiased methodical cause-effect relationship construction. In addition, thanks to a systematic rule-based generation of the causal loop diagram and the stock-flow chart, the D-ASBSC permits to effectively remedy to the infamous mental models restriction that has long been raised in System Dynamics modeling. {\textcopyright} Research India Publications.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029754284\&partnerID=40\&md5=2b1805b81731ebbb7b35691824759d36},
	author = {Chaker, F. and Manouar, A.E. and Idrissi, M.A.J.}
}
