Now showing 1 - 5 of 5
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Synthesizing Training Data with Generative Adversarial Networks: Towards the Design of a Data-Sharing Ecosystem Platform for Fraud Detection

2023-06-02 , Fabian Sven Karst , Mahei Li , Leimeister, Jan Marco

Financial fraud has a severe impact on the general population. While financial institutions have technological capabilities for fraud detection using intelligent AI systems, the delay until they have collected a sufficient size of fraudulent data to train their fraud detection models creates a costly vulnerability. One major challenge for quickly training data lies in the inability to share fraud detection training data with other financial institutions, due to data and privacy regulations. Thus, we create the concept for a data-sharing ecosystem platform that addresses data anonymity concerns by creating synthesized training data based on each institution’s fraud detection training data sets. We rely on the advantages of generative adversarial networks (GAN) to quickly construct a shared dataset for all ecosystem members. Applying design science research, this paper derives design knowledge based on financial fraud detection literature, data sharing between financial institutions, GANs and modular systems theory for the design of a plat-form architecture for data-sharing ecosystems.

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From Service Systems Engineering to Service Innovation - A Modeling Approach

2019-06-10 , Li, Mahei , Peters, Christoph

Due to the advent of digitization, service innovation has become even more important for both business and service research alike. Current service systems engineering approaches have employed a recombinant perspective that follows innovation mechanisms to leverage existing company resources for new service innovations. Employing these innovation mechanisms is still challenging, since there is little support on how to structure and identify these mechanisms. We propose a model-based service system engineering approach to structure existing resources into one formal model, enabling the formalization of service innovation mechanisms. The formalized service innovation mechanisms allow for a graphical illustration and enable future research to apply functions to analyze how innovation impacts entire or specific parts of service systems. Furthermore, the mathematical model enables an object-oriented value-driven perspective on service systems and is basis for graphical software tools. We contribute to literature by formalizing service innovations and its mechanisms in the context of service systems and by combining concepts of service innovation and service systems engineering. We do so by a) formalizing service innovation mechanisms and b) demonstrating the application of formal service innovations along one specific software implementation case. For practice, the service system model can with simulating the effects of service innovations.

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Sense of Control for Empowerment in Hybrid Intelligence Service Systems

2021-12-15 , Eilers, Karen , Li, Mahei

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A service system modelling approach

2018 , Li, Mahei

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Take the Wheel - Technology-driven Change in the Energy Sector

2019 , Li, Mahei , Müller, Jennifer , Ernst, Sissy-Josefina , Peters, Christoph