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A multifrequency image reconstruction for electrical impedance tomography to retain tissue spectral information
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“We are truly a global organization!” The documentary "American Factory" under the lens of the Transcultural Learning Model
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Exploratory Study on Sustainability in Agile Software Development
No full textSustainability is continuously gaining attention from different software research disciplines and organizations because of the impacts of human activities on the planet aided by software products and services. The process of creating and developing these software products and services through agile has gained significant attention with different guidelines and frameworks proposed to support sustainability. However, there is the challenge of a few concrete illustrations that exemplify how these software sustainability design guidelines and frameworks have been applied in agile practice, specifically Scrum by software development practitioners. This creates no common ground for software development practitioners to understand their role in promoting sustainability during software design and development. This paper explores integrating sustainability into agile software requirement gathering, focusing on the Scrum framework. The outcome presented in this study represents early results from an ongoing case study with an agile development team in the industry
COVID-19 in Female and Male Athletes : Symptoms, Clinical Findings, Outcome, and Prolonged Exercise Intolerance — A Prospective, Observational, Multicenter Cohort Study (CoSmo-S)
Get PDFEffect of Buteyko breathing technique on clinical and functional parameters in adult patients with asthma: a randomized, controlled study
Get PDFErgebnisse der Umfrage unter Studierenden im Wintersemester 2023/24 zu ihren Erfahrungen mit Künstlicher Intelligenz
Get PDFErgebnisse der Umfrage unter Studierenden im Wintersemester 2023/24 zu ihren Erfahrungen mit Künstlicher Intelligen
The future of the private banking sector: is AI application profitable for private banks?
No full textArtificial intelligence is a disruptive technology, offering increasingly more opportunities to companies. However, the low digital maturity of the private banking sector, makes it hard for private banks to take advantage of this opportunity. Simultaneously, customers are expecting more digital solutions, forcing companies to adapt their services.
The aim of this paper is to provide an overview, drawing conclusions about whether the implementation of AI technologies is profitable in the private banking sector.
This thesis is based on recent research about current possible applications and the respective benefits, risks and costs. Two use cases will be thoroughly analysed: the application of automated credit risk management systems and AI powered indexes. In the first case, the software NOLA 2.0 will be evaluated and used as a benchmark to highlight the positive and negative aspects deriving from AI credit risk management software. In the second case, the AI powered index AiPEXAR will be presented and compared to the most common ETF S&P 500, analysing the differences in their computation and their performance over time.
The analysis concluded that, even though the benefits substantially depend on the individual company, AI chatbots, customers' engagement, credit risk management software and banking apps are advantageous for private banks. Yet, the implementation of AI powered indexes may be precocious and therefore not yet profitable. It can also be concluded that for private banks, whose core competitive advantage lies in the expertise of the relationship managers, the digitalization of advisory may lead to unsatisfied customers
