Now showing 1 - 10 of 10
  • Publication
    FinDEx: A Synthetic Data Sharing Platform for Financial Fraud Detection
    The rising number of financial frauds inflicted in the last year more than 800 billion USD in damages on the global economy. Although financial institutions possess advanced AI systems for fraud detection, the time required to accumulate a sufficient volume of fraudulent data for training models creates a costly vulnerability. Combined with the inability to share fraud detection training data among institutions due to data and privacy regulations, this poses a major challenge. To address this issue, we propose the concept of a synthetic data-sharing ecosystem platform (FinDEx). This platform ensures data anonymity by generating synthesized training data based on each institution's fraud detection datasets. Various synthetic data generation techniques are employed to rapidly construct a shared dataset for all ecosystem members. Using design science research, this paper leverages insights from financial fraud detection literature, data sharing practices, and modular systems theory to derive design knowledge for the platform architecture. Furthermore, the feasibility of using different data generation algorithms such as generative adversarial networks, variational auto encoder and Gaussian mixture model was evaluated and different methods for the integration of synthetic data into the training procedure were tested. Thus, contributing to the theory at the intersection between fraud detection and data sharing and providing practitioners with guidelines on how to design such systems.
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  • Publication
    Generative AI in Customer Support Services: A Framework for Augmenting the Routines of Frontline Service Employees
    ( 2024-01-06)
    Philipp Reinhard
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    Customer support service employees are facing an increased workload, while artificial intelligence (AI) appears to possess the potential to change the way we work. With the advent of modern types of generative AI, new opportunities to augment frontline service employees have emerged. However, little is known about how to integrate generative AI in customer support service organizations and purposefully change service employee work routines. Following multi-method qualitative research, we performed a literature review, conducted workshops, and interviewed IT support agents, managers, and AI experts. Thereby, we examine AI augmentation for frontline service employees in the context of IT support to carve out where and how GenAI can be leveraged to develop more efficient and higher-quality customer support. Our resulting framework reveals that especially adapting solutions and retaining knowledge is subject to a high degree of AI augmentation.
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    Synthesizing Training Data with Generative Adversarial Networks: Towards the Design of a Data-Sharing Ecosystem Platform for Fraud Detection
    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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  • Publication
    Developing Lawful Technologies – A Revelatory Case Study on Design Patterns
    Higher legal standards regarding the data protection of individuals, such as the European General Data Protection Regulation, increase the pressure on developing lawful systems. In the development of technologies, not only developers are involved. It also requires knowledge from other stakeholders, such as legal experts, that lack technical knowledge but are required to understand IT artifacts. We see two strings that can benefit from the use of design patterns: first, the well-known use of design patterns to support developers in case of recurring problems. Second, we see potential that legal experts, who have to interact with and understand complicated, novel technologies, benefit from the same patterns. We conduct a revelatory case study using design patterns to develop and assess a smart learning assistant. We scaffolded the case interpretation through the human-centered view of socio-materiality and provide contributions concerning the use of design patterns in the development and assessment of lawful technologies.
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  • Publication
    Moving towards a Non-Dyadic View on Service Systems and its Operationalization – Applying the Hypergraph-based Service System Model
    In today’s VUCA world, that is characterized by high volatility, uncertainty, complexity and ambiguity, service provisioning is required to realize flexible and adaptable reconfiguration of service delivery systems and its stakeholders’ resources. However, services are often embedded in greater service systems and the context information of both customer and service provider form both its boundary conditions the suitable solution service. To capture the complexity and leverage the dynamic of service systems, we propose the formal service system model (SSM) method. Following general systems theory, we define boundaries for service delivery and show SSM’s applicability for ad-hoc service operations. We show its usefulness for structuring a service system for service operations, specifically scheduling, planning, and pricing of service provisioning. We contribute to service systems engineering by applying one generalizable mathematical model for both structuring and operationalizing service systems and provide insights in-to capturing the complex relationships of its components
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    Linking Strategy and Operations using a Service Business Model – a hypergraph theory-based approach
    Business models (BM) have become increasingly important and versatile abstract tools to describe businesses on both, a strategic, as well as operational level (Wirtz et al. 2015). These BMs are used to understand what a business does to remain competitive, strategically (Johnson et al. 2008). Existing research (Johnson et al. 2008; Wirtz et al. 2015) identified the importance of BMs for the success of businesses. Also, practice revealed that financially successful companies ascertain twice the level of importance than less successful companies (IBM, 2007). A BM is a conceptual and structural implementation of a business strategy and the foundation of business processes (Osterwalder and Pigneur, 2002). BMs include a strategy, input factors, processes, with an underlying financial model to ensure the profitability. In recent years BMs have become synonymous with entire companies. Literature shows a heterogeneous abstraction of BMs, sometimes referring to BMs as business unit or products (Wirtz et al. 2015). Service systems literature shows similar structures, with service systems referring to exchanges on an individual level, among business units or entire ecosystems (Chandler and Lusch 2015). We propose that a service systems perspective can systematically model businesses and capture its inherent complexities (Peters et al. 2015). The service business model (SBM) includes (1) the value proposition, which is the firm’s offering to the customer; (2) the value creation and delivery mechanisms, reflecting the value chain; (3) value capture and analysis of the BM and its constituent elements to understand how the firm generates profit. Our model, thus, captures the holistic characteristic of BM, while retaining the detailed information on how the business is constructed. Businesses are confronted with a complex, digitalized world, in which important service innovations are continuously emerging, which need to be designed and linked to the BM of a company, thus addressing the strategy to execution gap (Kaplan and Norton 2009). Typical BM tools, such as the business model canvas (Osterwalder et al. 2005), only provide a descriptive framework for structuring businesses, missing the interrelations of its BM elements. This is important for operational decision makers, who implement new service innovations. In sum, without a SBM that relates the high level strategic information to the detailed operations perspective, BMs only reflect half the picture. Hence, we develop a hypergraph theory-based underlying model for businesses to understand how the business works both from a strategic perspective, as well as from a detailed operational perspective. Our SBM makes value creation visible, relying on a systems perspective linking multi-dimensional input factors with set of activities and actors and thus capturing value proposition, value creation and delivery and value capture mechanisms (Li & Peters 2018). Attached table shows an overview of our SBM, which relies on a formally model (Li et al. 2018). It represents a base structure of businesses and can be used for operational purposes too (e.g.: scheduling, planning and cost analyses) and thus enables a high level strategic perspective to be integrated into the operational perspective, bridging the gap between strategy and execution for successful businesses.
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    Developing a Production Structure Model using Service-Dominant Logic – A hypergraph-based Modeling Approach
    To make a fundamental shift towards value orientation, manufacturing companies strategically move to integrate services into their portfolio. While manufacturing firms rely on production information systems as the backbone of their operations, these systems are based on product structure models (e.g., bill of materials). This poses a problem because services do not adhere to the goods-dominant perspective of product structures. To solve this divide, this paper proposes an integrative mathematical model for both production systems and service systems. This model draws upon concepts of service-dominant logic and is based on hypergraph theory. To illustrate that the production structure model includes both product structures and process structures, we further demonstrate that the production structure model can be transformed into either. Therefore, our theoretical contribution lies in introducing a structural model for production systems that is compatible with structures of a service system model. For practice, this model enables the development of production information systems that can plan and control products, services and hybrids.
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    A Hypergraph-based Modeling Approach for Service Systems
    Currently, research on service science has emerged as its own discipline, where service systems are its basic unit of analysis. However, without a clearly defined modeling approach for service systems, analyzing a service system is challenging. We therefore propose a conceptual hypergraph-based modeling approach, which can be used to model services for both traditional goods-dominant businesses, as well as service-businesses. We define key elements of a service system while drawing upon hypergraph theory and present three modeling properties which are required to model a service systems graph (SSG). The focus of SSGs is to describe the relationships between the various resources, actors and activities, thus configuring a service system. It provides the foundation for computer graphic simulations and database applications of service business structure for future research.
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    Towards Bridging the Gap between Business Model Innovation and Practice Using Hypergraph-based Modeling
    A hypergraph-based modeling of businesses bridges the gap between business model innovations and its implementation into enterprise solutions. By formalizing resources, actors, activities (processes) and functions into one model, their relationships are clearly defined, while encompassing both the data and processual structure. A database-based graphical tool supports system analysts and decision makers to structure and analyze their business model and corresponding value proposition. This model can thus be used for future implementations.
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  • Publication
    Designing a peer-based support system to support shakedown
    Many problems of software implementations appear after roll-out during the shakedown phase. Research have shown that peer advice ties are more effective and preferred by users than traditional IT support structures. However, large organizations are often shrouded in anonymity and individuals often don’t know which peer to ask for advice, resorting to help desks as a last resort. The paper addresses the challenges of peer advice ties as support structure by presenting a peer-based support system (PBSS) design to address emerging problems of individuals during shakedown. By applying design science research and theory of interaction as explanatory theory for peer advice to derive design requirements. Based on the informational, timeliness and contextual advantages of peer advice ties, we develop tentative design principles, which aids in identifying and creating interaction among peers. The contribution lies in prescriptive knowledge on how systems should be designed to support peer advice as support structures.
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