Abstract
This article describes the application area of predictive analytics within the context of value driver-based planning. We will briefly describe the technical principles and challenges and then turn our focus to aspects of realization based on practical examples. The key to value driver-oriented planning consists of connecting individual value drivers to logical value driver trees , i.e., mapping causal relationships to derive BS or P&L results and balance sheet items at a future point in time. The challenge here is not mapping causal relationships, but identifying value drivers and verifying valid relationships. The use of predictive analytics provides a sustainable and objective foundation for the process of identification and verification, which is illustrated in this article with practical examples including the design of required algorithms using R and the derivation of a future market potential for mortgage loans .
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Valjanow, S., Enzinger, P., Dinges, F. (2019). Leveraging Predictive Analytics Within a Value Driver-based Planning Framework. In: Liermann, V., Stegmann, C. (eds) The Impact of Digital Transformation and FinTech on the Finance Professional. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-23719-6_7
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DOI: https://doi.org/10.1007/978-3-030-23719-6_7
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