Now showing 1 - 9 of 9
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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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Gestaltungsdimensionen der Digitalisierung – Wie Dienstleistungssysteme den Wandel antreiben und welche Faktoren eine Rolle spielen

2020-10-03 , Grotherr, Christian , Li, Mahei , Schymanietz, Martin , Fritzsche, Albrecht , Semmann, Martin , Peters, Christoph , Böhmann, Tilo , Leimeister, Jan Marco , Möslein, Kathrin M.

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Digitale Servicesysteme

2019 , Li, Mahei , Peters, Christoph , Leimeister, Jan Marco , Zierau, Naim , Gassman, Oliver , Sutter, Philipp

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Einführung eines DSGVO-konformen Videokonferenzsystems in hessischen Schulen. Projektergebnisse des ZEVEDI Ad hoc-Vorhabens „Wechselkosten zum DSGVO-konformen VC-System des Schulportals Hessen“

2023 , Ernestine Dickhaut , Lasse Schaup , Mahei Li , Jan Marco Leimeister

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Künstliche Intelligenz und menschliche Kompetenz zur Automatisierung und Personalisierung von Dienstleistungen am Beispiel des Support

2020 , Li, Mahei , Bronner, Esther , Peters, Christoph , Leimeister, Jan Marco , Bruhn, Manfred , Hadwich, Karsten

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Einführung von Crowd-Based Support Dienstleistungen zur Verbesserung der Softwareeinführung

2018 , Li, Mahei Manhai , Billert, Matthias Simon , Dellermann, Dominik , Peters, Christoph , Leimeister, Jan Marco , Meyer, Kyrill , Klingner, Stephan , Zinke, Christian

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Nutzungszentrierte Gestaltung von HI-basierten Dienstleistungen am Beispiel des IT-Supports

2021-08-23 , Schmidt, Simon L. , Li, Mahei , Peters, Christoph , Leimeister, Jan Marco , Bruhn, Manfred , Hadwich, Karsten

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Nutzergenerierte Dienstleistungssysteme zur digitalen Transformation von Organisationen

2019 , Agarwal, Nivedita , Bästlein, Moritz , Böhmann, Tilo , Ernst, Sissy-Josefina , Fritzsche, Albrecht , Grotherr, Christian , Hoffmann, Holger , Klemm, Pablo , Leimeister, Jan Marco , Li, Mahei M. , Möslein, Kathrin M. , Peters, Christoph , Sarpong, Benjamin , Saxe, Sebastian , Schmidt, Thorsten , Schymanietz, Martin , Wurfbaum, Moritz S. , Semmann, Martin , Ziegler, Dirk

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Dynamic Solutions in Service Systems

2018 , Li, Mahei Manhai , Peters, Christoph , Leimeister, Jan Marco

With the rapidly increasing number and complexity of service demands, service providers need to become even more flexible and faster. To accommodate this, the service system needs to dynamically reconfigure its required resourced based on the context of both service providers and the customer. The resulting chosen service system configuration is called a dynamic solution. Our research question is therefore as follow: How can we implement the characteristic of dynamic solutions based on the service system model (SSM)? We demonstrate our model using a real-life citizen-based produce delivery service. We contribute by being able to quantify service system configurations and compare different configurations dynamically. Keywords: Service operations, operationalizing